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GPT-5.5 Pro

This isn't a patch on GPT-5.4. It thinks faster, uses fewer tokens, and keeps going when problems get messy.
GPT-5.5 ProTechflow Logo - Techflow X Webflow Template

GPT-5.5 Pro

OpenAI's newest flagship is a fully retrained base model built from the ground up for real work: agentic coding, complex knowledge tasks, computer use, and scientific research.

What actually changed and why it matters

Every major GPT-5.x release before this one was a post-training improvement layered on top of the same underlying model. GPT-5.5 is different: OpenAI rebuilt the base from scratch, which is why the capability jumps feel qualitative, not incremental.

Token-efficient reasoning

GPT-5.5 completes the same tasks as GPT-5.4 using significantly fewer tokens. That means lower cost, lower latency, and longer productive agent runs before context limits bite.

Agentic coding at scale

Powers OpenAI's Codex tool. NVIDIA deployed it internally to over 10,000 employees and reported debugging cycles dropping from days to hours, with multi-week experiments finishing overnight.

Computer use + intent parsing

Better at understanding what you actually want, not just what you literally said. It can handle a messy, multi-part brief, build its own plan, and navigate ambiguity across real software environments.

Knowledge work breadth

Financial modeling, legal drafting, investment-banking tasks, data analysis, document creation — GDPval covers 44 occupations across 9 industries, and GPT-5.5 scores near the top of the public leaderboard.

Scientific research assist

OpenAI's chief research officer says GPT-5.5 shows meaningful gains in scientific and technical workflows. Early use cases include drug discovery pipelines and mathematical research under expert oversight.

Hardened safety layer

GPT-5.5 introduces stricter classifiers for cybersecurity risk, third-party red-team testing for both cyber and bio risks, and tighter controls around sensitive requests, built on safeguards first deployed with GPT-5.2.

API Pricing

  • Input: $39 / 1M tokens
  • Output: $234 / 1M tokens

Benchmark performance

Numbers without context are marketing. Here's how GPT-5.5 and GPT-5.5 Pro sit against the current competitive field, with notes on where rivals still hold an edge.

Who it's built for

GPT-5.5 Pro isn't the right tool for every situation. Here's an honest read on where it earns its premium, and where alternatives make more sense.

GDPval
84.9%
Terminal-Bench 2.0
82.7%
OSWorld
78.7%
FinanceAgent
60.0%
OfficeQA Pro
54.1%
Tau2-bench Telecom
98.0%

Strong fit

  • Agentic software teams: if your developers are already running Codex or API-based agents, GPT-5.5 cuts debug cycles and handles complex multi-file codebases better than any prior OpenAI model.
  • Knowledge-intensive enterprise work: financial analysis, legal drafting, consulting deliverables. The GDPval benchmark covers exactly these occupations, and the results hold up in real deployments.
  • Scientific research teams: early evidence from OpenAI and partner organizations points to genuine value in hypothesis exploration and literature synthesis under expert human oversight.
  • Computer use pipelines: operating software autonomously, navigating GUIs, completing multi-step workflows across applications without constant hand-holding.

Where rivals have the edge

  • Complex multi-file GitHub work: Claude Opus 4.7 still leads on SWE-bench Pro (64.3% vs 58.6%). For pure multi-file coding precision, that gap is real.
  • Very long context inputs: Google Gemini 3.1 Pro's 2M token context window remains a genuine differentiator for workloads that involve enormous document sets.
  • Cost-sensitive inference at scale: For high-volume commodity tasks, that price difference compounds quickly.

Common questions

Is GPT-5.5 the same as GPT-5.4 with better fine-tuning?

No. GPT-5.5 is a fully retrained base model, which sets it apart from the GPT-5.1 through 5.4 releases that were primarily post-training improvements layered on the same underlying weights. The architecture-level retraining is why capability gains feel qualitative rather than marginal.

What's the difference between GPT-5.5 and GPT-5.5 Pro?

GPT-5.5 is the standard model available to Plus and above. GPT-5.5 Pro is the extended-reasoning variant, with adjustable reasoning effort settings (medium, high, xhigh), available to Pro, Business, and Enterprise tiers. Pro is the version OpenAI positions for demanding research and complex professional tasks.

Will GPT-5.5 replace GPT-5.4 in existing API integrations?

Not automatically. The API uses model strings and snapshot aliases. You'll need to explicitly update to gpt-5.5 or gpt-5.5-pro once your integration is ready for the capability and safety profile changes that come with the new model.

What actually changed and why it matters

Every major GPT-5.x release before this one was a post-training improvement layered on top of the same underlying model. GPT-5.5 is different: OpenAI rebuilt the base from scratch, which is why the capability jumps feel qualitative, not incremental.

Token-efficient reasoning

GPT-5.5 completes the same tasks as GPT-5.4 using significantly fewer tokens. That means lower cost, lower latency, and longer productive agent runs before context limits bite.

Agentic coding at scale

Powers OpenAI's Codex tool. NVIDIA deployed it internally to over 10,000 employees and reported debugging cycles dropping from days to hours, with multi-week experiments finishing overnight.

Computer use + intent parsing

Better at understanding what you actually want, not just what you literally said. It can handle a messy, multi-part brief, build its own plan, and navigate ambiguity across real software environments.

Knowledge work breadth

Financial modeling, legal drafting, investment-banking tasks, data analysis, document creation — GDPval covers 44 occupations across 9 industries, and GPT-5.5 scores near the top of the public leaderboard.

Scientific research assist

OpenAI's chief research officer says GPT-5.5 shows meaningful gains in scientific and technical workflows. Early use cases include drug discovery pipelines and mathematical research under expert oversight.

Hardened safety layer

GPT-5.5 introduces stricter classifiers for cybersecurity risk, third-party red-team testing for both cyber and bio risks, and tighter controls around sensitive requests, built on safeguards first deployed with GPT-5.2.

API Pricing

  • Input: $39 / 1M tokens
  • Output: $234 / 1M tokens

Benchmark performance

Numbers without context are marketing. Here's how GPT-5.5 and GPT-5.5 Pro sit against the current competitive field, with notes on where rivals still hold an edge.

Who it's built for

GPT-5.5 Pro isn't the right tool for every situation. Here's an honest read on where it earns its premium, and where alternatives make more sense.

GDPval
84.9%
Terminal-Bench 2.0
82.7%
OSWorld
78.7%
FinanceAgent
60.0%
OfficeQA Pro
54.1%
Tau2-bench Telecom
98.0%

Strong fit

  • Agentic software teams: if your developers are already running Codex or API-based agents, GPT-5.5 cuts debug cycles and handles complex multi-file codebases better than any prior OpenAI model.
  • Knowledge-intensive enterprise work: financial analysis, legal drafting, consulting deliverables. The GDPval benchmark covers exactly these occupations, and the results hold up in real deployments.
  • Scientific research teams: early evidence from OpenAI and partner organizations points to genuine value in hypothesis exploration and literature synthesis under expert human oversight.
  • Computer use pipelines: operating software autonomously, navigating GUIs, completing multi-step workflows across applications without constant hand-holding.

Where rivals have the edge

  • Complex multi-file GitHub work: Claude Opus 4.7 still leads on SWE-bench Pro (64.3% vs 58.6%). For pure multi-file coding precision, that gap is real.
  • Very long context inputs: Google Gemini 3.1 Pro's 2M token context window remains a genuine differentiator for workloads that involve enormous document sets.
  • Cost-sensitive inference at scale: For high-volume commodity tasks, that price difference compounds quickly.

Common questions

Is GPT-5.5 the same as GPT-5.4 with better fine-tuning?

No. GPT-5.5 is a fully retrained base model, which sets it apart from the GPT-5.1 through 5.4 releases that were primarily post-training improvements layered on the same underlying weights. The architecture-level retraining is why capability gains feel qualitative rather than marginal.

What's the difference between GPT-5.5 and GPT-5.5 Pro?

GPT-5.5 is the standard model available to Plus and above. GPT-5.5 Pro is the extended-reasoning variant, with adjustable reasoning effort settings (medium, high, xhigh), available to Pro, Business, and Enterprise tiers. Pro is the version OpenAI positions for demanding research and complex professional tasks.

Will GPT-5.5 replace GPT-5.4 in existing API integrations?

Not automatically. The API uses model strings and snapshot aliases. You'll need to explicitly update to gpt-5.5 or gpt-5.5-pro once your integration is ready for the capability and safety profile changes that come with the new model.

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