GPT-5.5 vs Claude Opus 4.7: Which AI model is better for your workload?

Two rows deserve extra caution. For Terminal-Bench 2.0, LLM Stats and other summaries report Claude Opus 4.7 at 69.4%, while another comparison lists GPT-5.5 at 82.7% but does not provide a public Opus number . For MCP Atlas, BenchLM's public snapshot shows Claude Opus 4.7 at 77.3% and GPT-5.5 at 75.3%, while other reporting cites Claude at 79.1% against the same 75.3% GPT-5.5 figure .

Even with those caveats, the direction is fairly consistent: GPT-5.5 looks stronger for terminal-style execution; Claude Opus 4.7 looks stronger for Model Context Protocol and tool orchestration.

Coding: do not stop at SWE-Bench Verified

SWE-bench tests whether a model can resolve real GitHub issues, and the Pro variant is described as the harder version with more complex issues . That distinction matters.

On SWE-Bench Verified, GPT-5.5 scores 88.7% and Claude Opus 4.7 scores 87.6%, which is best read as a practical tie . If your coding tasks are mostly small, well-scoped fixes, that benchmark alone does not strongly favor either model.

SWE-Bench Pro gives a more useful signal for difficult engineering work. Claude Opus 4.7 is reported at 64.3% versus GPT-5.5 at 58.6%, a 5.7-point lead . The Pro set is also more demanding: one overview says SWE-Bench Verified has 500 tasks across 12 Python repositories, while SWE-Bench Pro has 1,865 tasks across 41 repositories spanning Python, Go, TypeScript and JavaScript; average files changed rises from about one file to 4.1 files .

For teams building coding agents that need to repair pull requests, modify several files, refactor code or reason across a large repository, Claude Opus 4.7 should be high on the shortlist. MindStudio's coding comparison also says Opus 4.7 performs better on tasks that require broader architectural reasoning across large codebases .

Agents and tools: GPT-5.5 for terminal work, Claude for orchestration

If the workflow looks like a command-line session, GPT-5.5 has the stronger benchmark case. Terminal-Bench 2.0 is reported at 82.7% for GPT-5.5 and 69.4% for Claude Opus 4.7 in several summaries . Because one public comparison does not list an Opus number for that row, it is safer to read this as a directional signal rather than an absolute leaderboard verdict .

For agents that must coordinate external services, Claude's case is stronger. MCP Atlas is a benchmark for tool-calling over Model Context Protocol integrations and external tools . BenchLM's public snapshot puts Claude Opus 4.7 at 77.3% and GPT-5.5 at 75.3% . Other reporting frames the same comparison as 79.1% versus 75.3% .

In plain English: if your agent mostly runs shell commands, navigates files and executes step-by-step computer tasks, start with GPT-5.5. If it needs to reliably sequence API calls, services and tools, start with Claude Opus 4.7.

Reasoning and research: math is not the same as broad exams

Reasoning is too broad a label to be useful on its own. On OpenAI's GPT-5.5 table, GPT-5.5 leads Claude Opus 4.7 on FrontierMath Tier 1–3, 51.7% to 43.8%, and on FrontierMath Tier 4, 35.4% to 22.9% . For math-heavy reasoning, GPT-5.5 is the clearer pick.

Other reasoning benchmarks tell a different story. On GPQA Diamond, the models are almost tied: GPT-5.5 scores 93.6% and Claude Opus 4.7 scores 94.2% . On Humanity's Last Exam, Claude leads in both settings: 46.9% versus GPT-5.5's 41.4% without tools, and 54.7% versus 52.2% with tools .

For web-style research, GPT-5.5 has the advantage in the reported BrowseComp numbers: 84.4% versus Claude Opus 4.7's 79.3% .

Which model should you choose?

Choose GPT-5.5 if:

• Your workflow involves terminal execution, shell automation, command-line agents or step-by-step computer work; GPT-5.5 is ahead in reported Terminal-Bench 2.0 comparisons .
• Your workload is math-heavy; GPT-5.5 leads Claude Opus 4.7 on both FrontierMath Tier 1–3 and Tier 4 .
• You need browsing-heavy research or BrowseComp-style analysis; GPT-5.5 is reported at 84.4% versus Claude Opus 4.7 at 79.3% .

Choose Claude Opus 4.7 if:

• Your main workload is complex codebase modification, multi-file bug fixing or production coding agents; Claude leads GPT-5.5 on SWE-Bench Pro, 64.3% to 58.6% .
• You are building agents that need MCP, API or tool orchestration; MCP Atlas snapshots put Claude Opus 4.7 ahead of GPT-5.5 .
• Your tasks depend on architectural reasoning across large repositories; MindStudio's comparison says Opus 4.7 is stronger on that kind of large-codebase reasoning .

Read the benchmarks carefully

Public benchmark numbers are not the same as production truth. Anthropic's Claude Opus 4.7 release notes mention harness changes, internal implementations and methodology updates, and say some scores are not directly comparable with public leaderboard scores . A builder-focused GPT-5.5 summary also flags that several benchmark scores are OpenAI-reported and lack third-party replication .

The practical move is to run a small internal evaluation before committing. Use recent tickets, representative repositories, your real tool stack, your actual prompts and clear pass/fail criteria. Leaderboards can tell you where to begin; your workload should decide where you end up.

Verdict

GPT-5.5 looks like the better default for broad execution, terminal automation, math-heavy reasoning and BrowseComp-style research . Claude Opus 4.7 looks like the stronger candidate for harder software engineering, production coding agents and multi-tool orchestration .

So the honest conclusion is not GPT-5.5 wins or Claude wins. It is: GPT-5.5 is stronger in execution, math and research signals; Claude Opus 4.7 is stronger in hard coding and tool-agent workflows.