Claude Opus 4.7 vs GPT-5.5
Two April 2026 flagships, both built for coding — but they win on different things. Here is the side-by-side, with a clear verdict.
Claude Opus 4.7 vs GPT-5.5: side-by-side
| Claude Opus 4.7 | GPT-5.5 "Spud" | |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Released | 16 April 2026 | 23 April 2026 |
| Context window | 1M tokens | 1M tokens (400K in Codex CLI) |
| Max output | Up to 128K tokens | Not specified |
| API price (per 1M) | $5 in / $25 out | $5 in / $30 out |
| Built for | Code quality, vision, long-context work | Agentic coding, computer use, deep research |
| Standout | 87.6% SWE-bench Verified · strong vision | Codex integration · agentic reliability |
Benchmark comparison
The two models are measured on overlapping but not identical suites. On the benchmark they share, Opus 4.7 leads.
| Benchmark | Claude Opus 4.7 | GPT-5.5 | Winner |
|---|---|---|---|
| SWE-bench Pro | 64.3% | 58.6% | Opus 4.7 |
| SWE-bench Verified | 87.6% | — | Opus 4.7 |
| Terminal-Bench 2.0 | — | 82.7% | GPT-5.5 |
Key takeaway
Opus 4.7 has the edge on code-quality benchmarks; GPT-5.5 owns agentic, command-line task completion. The honest read: they are not competing for the same job, so the right pick depends on whether you need clean code or reliable multi-step automation.
Where Claude Opus 4.7 wins
Opus 4.7 leads the shared coding benchmark by nearly 6 points and posts an 87.6% SWE-bench Verified score that puts it ahead of every rival flagship. It also has substantially stronger vision — high-resolution image support up to 2,576 pixels on the long edge — and Anthropic reports the most consistent long-context performance of any model tested. For code review, dense screenshot reading and tasks where output correctness matters more than autonomous tool use, Opus is the safer pick.
Where GPT-5.5 wins
GPT-5.5 is built around agentic reliability — chaining many steps together without drifting — and is integrated tightly into the Codex environment. Its 82.7% on Terminal-Bench 2.0 reflects strength at command-line, computer-use style tasks. If your workflow is an autonomous agent operating tools across many steps, GPT-5.5 is the model designed for it.
Price comparison
Both models charge $5 per 1M input tokens. Opus 4.7 is cheaper on output — $25 vs $30 per 1M — and supports prompt caching that can cut costs up to 90%. One caveat: Opus 4.7's new tokenizer can produce up to 35% more tokens for the same text, so compare end-to-end request costs rather than just the rate card.
Which should you use?
- Code quality, review, vision tasks → Claude Opus 4.7.
- Agentic automation and Codex workflows → GPT-5.5.
- Long-context consistency → Claude Opus 4.7.
- Lowest cost → neither — look at DeepSeek V4 or Kimi K2.6.
Full Claude Opus 4.7 overview Full GPT-5.5 overview
Frequently asked questions
Is Claude Opus 4.7 better than GPT-5.5?
Claude Opus 4.7 leads on raw coding benchmarks — 64.3% vs 58.6% on SWE-bench Pro — and has stronger vision and long-context consistency. GPT-5.5 leads on agentic, multi-step tool use, scoring 82.7% on Terminal-Bench 2.0, and integrates tightly with the Codex environment. Opus wins code quality; GPT-5.5 wins agentic reliability.
Which is cheaper?
Both cost $5 per million input tokens. Claude Opus 4.7 is cheaper on output at $25 per million versus GPT-5.5's $30. However, Opus 4.7 ships with a new tokenizer that can generate up to 35% more tokens, so the real per-request cost can be higher than the rate card suggests.
Which has a bigger context window?
Both Claude Opus 4.7 and GPT-5.5 have a 1 million token context window. GPT-5.5's context drops to 400,000 tokens inside the Codex CLI.
Which is better for coding?
It depends on the task. Claude Opus 4.7 scores higher on SWE-bench Pro (64.3%) and SWE-bench Verified (87.6%), so it leads on code quality. GPT-5.5 leads on agentic, multi-step coding inside the Codex environment, scoring 82.7% on Terminal-Bench 2.0.