GPT-5.5 and Claude Opus 4.7 are two of the most important model choices for teams doing serious coding, agentic workflows, and long-running knowledge work in 2026. Both vendors are positioning these models as more than chat upgrades. They are selling them as systems that can stay on task, use tools, and complete higher-value work with less supervision.
That overlap is exactly why the comparison matters. If you are choosing between them, the real question is not which model wins a headline benchmark. It is which one fits your workload, your deployment constraints, and your cost tolerance.
The short answer
If your priority is agentic breadth across coding, browsing, computer-use style workflows, and knowledge work, GPT-5.5 currently has the stronger official story. OpenAI’s release positions it as a broader work model, and its published comparison table shows strong results on Terminal-Bench 2.0, BrowseComp, OSWorld-Verified, Toolathlon, and CyberGym.
If your priority is hard software engineering work and you want a premium model with a somewhat lower output token price, Claude Opus 4.7 still looks highly competitive. OpenAI’s own comparison table shows Opus 4.7 ahead of GPT-5.5 on SWE-Bench Pro, and Anthropic is explicitly framing Opus 4.7 as a model for difficult, long-running coding tasks that previously needed tighter human supervision.
So the practical answer is simple:
- Choose GPT-5.5 if you want the more general frontier model for coding plus broader agent work.
- Choose Claude Opus 4.7 if your center of gravity is difficult engineering tasks and you already like Anthropic’s coding workflow stack.
What the official benchmark picture says
OpenAI’s GPT-5.5 launch page publishes a direct comparison against Claude Opus 4.7 on several evaluations. On that table, GPT-5.5 leads Opus 4.7 on:
- Terminal-Bench 2.0: 82.7% vs 69.4%
- BrowseComp: 84.4% vs 79.3%
- OSWorld-Verified: 78.7% vs 78.0%
- CyberGym: 81.8% vs 73.1%
But the same OpenAI table shows Claude Opus 4.7 ahead on SWE-Bench Pro, with Opus at 64.3% versus GPT-5.5 at 58.6%. That is the most important caveat in the whole comparison, because many buyers care more about software engineering depth than broad tool-use versatility.
The right reading is not that one model dominates everything. It is that the two models appear to be optimized a bit differently. GPT-5.5 looks stronger when the workload resembles a multi-tool, multi-step work system. Opus 4.7 still looks especially credible when the job is difficult engineering execution.
How the vendors are positioning them
OpenAI’s GPT-5.5 pitch
OpenAI describes GPT-5.5 as a model that can take on “real work” across coding, online research, documents, spreadsheets, data analysis, and software operation. That is a wider positioning than “best coding model.” It suggests OpenAI wants GPT-5.5 to be the default frontier choice for agentic professional workflows, not just a developer specialist.
That matters if your team wants one premium model that can stretch across engineering, operations, internal research, and workflow automation.
Anthropic’s Claude Opus 4.7 pitch
Anthropic’s positioning is more focused. Opus 4.7 is presented as a notable step up from Opus 4.6 for advanced software engineering, especially on hard coding tasks that benefit from rigor, instruction-following, and self-verification. Anthropic also highlights stronger vision and higher-quality professional outputs for interfaces, slides, and docs.
That makes Opus 4.7 feel like the premium choice for teams that want careful execution, especially inside Anthropic-oriented coding and enterprise workflows.
Pricing is close on input, different on output
| Model | Input price | Cached input | Output price |
|---|---|---|---|
| GPT-5.5 | $5.00 / 1M tokens | $0.50 / 1M | $30.00 / 1M |
| Claude Opus 4.7 | $5.00 / 1M tokens | Not the main headline comparison | $25.00 / 1M |
The pricing gap is not huge on input, but it is material on output. If your workload produces long answers, long code diffs, or many agent-generated artifacts, Opus 4.7 can be meaningfully cheaper on the output side.
OpenAI’s counterargument is token efficiency. GPT-5.5 is being positioned as more token-efficient than GPT-5.4 in real coding tasks, and OpenAI also offers Batch and Flex discounts plus a faster Codex mode for certain workflows. If that efficiency claim holds in your stack, the raw output price difference may not tell the whole story.
This is why production evaluation matters. A model that is 20% more expensive per output token can still be cheaper per completed task if it takes fewer turns, emits fewer retries, or solves the task cleanly the first time.
Availability and deployment differences
GPT-5.5 is available across ChatGPT, Codex, and the OpenAI API. OpenAI also says the model is available on Amazon Bedrock, which can matter for enterprises standardizing on AWS procurement, governance, and regional deployment controls.
Claude Opus 4.7 is available across Claude products, the Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry. That gives Anthropic a strong multi-cloud distribution story, especially for enterprises that want to stay flexible across cloud providers.
In other words, deployment flexibility is good on both sides. The real difference is more about which broader platform you want to buy into: OpenAI’s agent-and-workflow stack or Anthropic’s coding-and-enterprise stack.
Which teams should choose GPT-5.5
- Teams building general-purpose agent systems, not just coding assistants
- Organizations that want one flagship model for coding, browsing, docs, analysis, and computer-use style workflows
- Buyers already leaning into OpenAI Codex, ChatGPT business workflows, or Bedrock-based OpenAI deployments
- Teams where benchmark strength on terminal work, browsing, and broader task completion matters more than pure SWE benchmark leadership
Which teams should choose Claude Opus 4.7
- Engineering-heavy teams optimizing for difficult software tasks
- Organizations that already prefer Claude Code, Anthropic APIs, or Anthropic’s enterprise posture
- Buyers sensitive to output-token costs
- Teams that want a premium model with a reputation for careful execution and strong instruction fidelity
The real decision is workflow shape
The biggest mistake is treating this as a pure IQ contest. These are not just two models fighting for benchmark bragging rights. They support different operating assumptions.
GPT-5.5 looks like the stronger choice for a team that wants an AI system to move across tools and work surfaces as a broad work engine.
Claude Opus 4.7 looks like the stronger choice for a team that wants a premium engineering workhorse and values Anthropic’s coding orientation.
That is why the most useful eval is still your own. If your team writes long code diffs, reviews repositories, produces design docs, searches the web, or works inside secure enterprise tooling, your best model is the one that completes those tasks with the best mix of reliability, speed, and cost. On paper, both are top-tier. In practice, they are top-tier for slightly different reasons.