After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
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After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed «Spud» internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.
And to likely no one’s surprise, it’s hardly a «potato» in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic’s and Google’s latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie).
«It’s definitely our strongest model yet on coding, both measured by benchmarks and based on the feedback that we’ve gotten from trusted partners, as well as our own experience,» explained Amelia «Mia» Glaese, VP of Research at OpenAI, in a video call with journalists ahead of the launch earlier today.
OpenAI positions GPT-5.5 as a fundamental redesign of how intelligence interacts with a computer’s operating system and professional software stacks.
«What is really special about this model is how much more it can do with less guidance,» said OpenAI co-founder and president Greg Brockman on the same call. «It’s way more intuitive to use. It can look at an unclear problem and figure out what needs to happen next.»
Brockman proceeded to emphasize the areas in which users can expect to see gains from using GPT-5.5 compared to OpenAI’s prior state-of-the-art model, GPT-5.4, which remains available (for now) to users and enterprises at half the API cost of its new successor.
«It’s extremely good at coding,» Brockman said of GPT-5.5. «It’s also great at broader computer work, computer use, scientific research—these kinds of applications that are very intelligent bottlenecks.»
OpenAI CEO and-cofounder Sam Altman also weighed in on the launch and the company’s philosophy in a post on X, writing, in part: «We want our users to have access to the best technology and for everyone to have equal opportunity.»
The model is available in two variants: GPT-5.5 and GPT-5.5 Pro, distinguished by the latter offering enhanced precision and specialized logic for handling the most rigorous cognitive demands.
While the standard version serves as the versatile flagship for general intelligence tasks, the Pro model is architected specifically for high-stakes environments such as legal research, data science, and advanced business analytics where accuracy is paramount. This premium tier provides noticeably more comprehensive and better-structured responses, supported by specialized latency optimizations that ensure high-quality performance during complex, multi-step workflows.
Unfortunately for third-party software developers, API access is not yet available for either GPT-5.5 nor GPT-5.5 Pro and will be coming «very soon,» according to the company’s announcement blog post.
«API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale,» OpenAI writes.
For the time being, GPT-5.5 is available only to paying subscribers of the ChatGPT Plus ($20 monthly), Pro ($100-$200 monthly), Business, and Enterprise users, with GPT-5.5 Pro access starting at the Pro tier and upwards.
A focus on agency
At the core of GPT-5.5 is a focus on «agentic» performance—specifically in coding, computer use, and scientific research.
Unlike its predecessors, which often required granular, step-by-step prompting to avoid «hallucinating» a path forward, GPT-5.5 is designed to handle messy, multi-part tasks autonomously.
It excels at researching online, debugging complex codebases, and moving between documents and spreadsheets without human intervention.
One of the most significant technical leaps is the model’s efficiency. While larger models typically suffer from increased latency, GPT-5.5 matches the per-token latency of the previous GPT-5.4 while delivering a higher level of intelligence.
This was achieved through a deep hardware-software co-design. OpenAI served GPT-5.5 on NVIDIA GB200 and GB300 NVL72 systems, utilizing custom heuristic algorithms—written by the AI itself—to partition and balance work across GPU cores.
This optimization reportedly increased token generation speeds by over 20%.For high-stakes reasoning, the «GPT-5.5 Thinking» mode in ChatGPT provides smarter, more concise answers by allowing the model more internal «compute time» to verify its own assumptions before responding.
This capability is particularly visible in the model’s performance on «Expert-SWE,» an internal OpenAI benchmark for long-horizon coding tasks with a median human completion time of 20 hours. GPT-5.5 notably outperformed GPT-5.4 on this metric while using significantly fewer tokens.
Benchmarks show OpenAI has retaken the lead in most powerful publicly available LLM over Claude Opus 4.7 (but the unreleased Mythos still outperforms it)
The market for leading U.S.-made frontier models has become an increasingly tight race between OpenAI, Anthropic, and Google.
Literally a week ago to the date, OpenAI rival Anthropic released Opus 4.7, its most powerful generally available model, to the public, taking over the leaderboard in terms of the number of third-party benchmark tests in which it has the lead.
Yet today, GPT-5.5 has surpassed it and even Anthropic’s heavily restricted, more powerful model Claude Mythos Preview, albeit only on one benchmark, Terminal-Bench 2.0, which tests «a model’s ability to navigate and complete tasks in a sandboxed terminal environment.»
GPT-5.5 achieved 82.7% accuracy on Terminal-Bench 2.0, easily surpassing Opus 4.7 (69.4%) and narrowly beating the Mythos Preview (82.0%).
However, in multidisciplinary reasoning without tools, the landscape is more competitive. On Humanity’s Last Exam without tools, GPT-5.5 Pro scored 43.1%, trailing behind Opus 4.7 (46.9%) and Mythos Preview (56.8%).
|
Benchmark |
GPT-5.5 |
Claude Opus 4.7 |
Gemini 3.1 Pro |
Mythos Preview* |
|
Terminal-Bench 2.0 |
82.7 |
69.4 |
68.5 |
82.0 |
|
Expert-SWE (Internal) |
73.1 |
— |
— |
— |
|
GDPval (wins or ties) |
84.9 |
80.3 |
67.3 |
— |
|
OSWorld-Verified |
78.7 |
78.0 |
— |
79.6 |
|
Toolathlon |
55.6 |
— |
48.8 |
— |
|
BrowseComp |
84.4 |
79.3 |
85.9 |
86.9 |
|
FrontierMath Tier 1–3 |
51.7 |
43.8 |
36.9 |
— |
|
FrontierMath Tier 4 |
35.4 |
22.9 |
16.7 |
— |
|
CyberGym |
81.8 |
73.1 |
— |
83.1 |
|
Tau2-bench Telecom (original prompts) |
98.0 |
— |
— |
— |
|
OfficeQA Pro |
54.1 |
43.6 |
18.1 |
— |
|
Investment Banking Modeling Tasks (Internal) |
88.5 |
— |
— |
— |
|
MMMU Pro (no tools) |
81.2 |
— |
80.5 |
— |
|
MMMU Pro (with tools) |
83.2 |
— |
— |
— |
|
GeneBench |
25.0 |
— |
— |
— |
|
BixBench |
80.5 |
— |
— |
— |
|
Capture-the-Flags challenge tasks (Internal) |
88.1 |
— |
— |
— |
|
ARC-AGI-2 (Verified) |
85.0 |
75.8 |
77.1 |
— |
|
SWE-bench Pro (Public) |
58.6 |
64.3 |
54.2 |
77.8 |
This suggests that while OpenAI is winning on «computer use» and «agency,» other models may still hold an edge in pure, zero-shot academic knowledge.
It is important to clarify that Mythos Preview is not a generally available product; Anthropic has classified it as a strategic defensive asset due to its high cybersecurity risks, restricting its access to a small, limited audience of trusted partners and government agencies.
Because Mythos is excluded from broad commercial use, the primary market competition remains between GPT-5.5, Gemini 3.1 Pro, and Claude Opus 4.7.
So when it comes to models that the general public can access, GPT-5.5 has retaken the crown for OpenAI, achieving the state-of-the-art across 14 benchmarks compared to 4 for Claude Opus 4.7 and 2 for Google Gemini 3.1 Pro.
It dominates in agentic computer use, economic knowledge work (GDPval), specialized cybersecurity (CyberGym), and complex mathematics (Frontier Math).
In comparison, Claude Opus 4.7 leads on software engineering and reasoning without tools, while Gemini 3.1 Pro leads in three categories, specifically excelling in academic reasoning and financial analysis.
Increased costs for users
The shift in intelligence comes with a significant price increase for API developers, according to material OpenAI shared ahead of the model’s public release.
OpenAI has effectively doubled the entry price for its flagship model compared to the previous generation, and again double it from there for the most-cutting edge variant of the model, GPT-5.5 Pro:
|
Model |
Input Price (per 1M tokens) |
Output Price (per 1M tokens) |
|
GPT-5.4 |
$2.50 |
$15.00 |
|
GPT-5.5 |
$5.00 |
$30.00 |
|
GPT-5.5 Pro |
$30.00 |
$180.00 |
To mitigate these costs, OpenAI emphasizes that GPT-5.5 is more «token efficient,» meaning it uses fewer tokens to complete the same task compared to GPT-5.4.
For users requiring speed over depth, OpenAI also introduced a Fast mode in Codex, which generates tokens 1.5x faster but at a 2.5x price premium.
The «mini» and «nano» tiers seen in the GPT-5.4 era (priced at $0.75 and $0.20 per 1M input tokens respectively) currently have no GPT-5.5 equivalent, though the company notes that GPT-5.5 is rolling out to all subscription tiers, including Plus, Pro, and Enterprise.
Licensing and the ‘cyber-permissive’ frontier
OpenAI’s approach to safety and licensing for GPT-5.5 introduces a novel concept: Trusted Access for Cyber. Because the model is now capable of identifying and patching advanced security vulnerabilities, OpenAI has implemented stricter «cyber-risk classifiers» for general users.
For legitimate security professionals, however, OpenAI is offering a specialized «cyber-permissive» license. This program allows verified defenders—those responsible for critical infrastructure like power grids or water supplies—to use models like GPT-5.4-Cyber or unrestricted versions of GPT-5.5 with fewer refusals for security-related prompts.
This dual-use framework acknowledges that while AI can accelerate cyber defense, it can also be weaponized. Under OpenAI’s Preparedness Framework, GPT-5.5 is classified as «High» risk for biological and cybersecurity capabilities.
To manage this, API deployments currently require different safeguards than the consumer-facing ChatGPT, and OpenAI is working with government partners to ensure these tools are used to strengthen—not undermine—digital resilience.
Initial reactions: losing access feels like having a ‘limp amputated’
The early feedback from power users and engineers suggests that GPT-5.5 has crossed a psychological threshold in AI utility. For developers, the model’s ability to maintain «conceptual clarity» across massive codebases is its standout feature.
«The first coding model I’ve used that has serious conceptual clarity,» noted Dan Shipper, CEO of Every.
Shipper tested the model by asking it to debug a complex system failure that had previously required a team of human engineers to rewrite; GPT-5.5 produced the same fix autonomously. Similarly, Pietro Schirano, CEO of MagicPath, described a «step change» in performance when the model successfully merged a branch with hundreds of refactor changes into a main branch in a single, 20-minute pass.Perhaps the most visceral reaction came from an anonymous engineer at NVIDIA, who had early access to the model:
«Losing access to GPT-5.5 feels like I’ve had a limb amputated».
This sentiment is echoed in the scientific community. Derya Unutmaz, a professor at the Jackson Laboratory for Genomic Medicine, used GPT-5.5 Pro to analyze a dataset of 28,000 genes, producing a report in minutes that would have normally taken his team months.
Brandon White, CEO of Axiom Bio, went further, stating that if OpenAI continues this pace, «the foundations of drug discovery will change by the end of the year».
GPT-5.5 is more than an incremental update; it is a tool designed for a world where humans delegate entire workflows rather than single prompts. While the costs are higher and the safety guardrails tighter, the performance gains in agentic work suggest that AI is finally moving from the chat box and into the operating system.
Perhaps most astonishingly of all, it’s not even hearing the end of the scaling limits — whereupon models are trained on more and more GPUs — according to researchers at the company.
«We actually still have headroom to train significantly smarter models than this,» said OpenAI chief scientist Jakub Pachocki.
