Claude Opus 4.7 is the better pure coding pick by the current public SWE-Bench Pro number: 64.3% vs GPT-5.5's 58.6%. GPT-5.5 is the stronger OpenAI/Codex ecosystem choice, with excellent Terminal-Bench performance, computer-use oriented workflows, and a 1M API context window. Pick Opus 4.7 when coding ceiling matters most. Pick GPT-5.5 when your stack, agents, or team workflows already center on OpenAI.
AnthropicPremium
Claude Opus 4.7
Previous Opus flagship, now superseded by Claude Opus 4.8 at the same price.
Winner
VS
OpenAIPremium
GPT-5.5
Best OpenAI flagship for agentic coding, research, and computer-use work.
At a glance
Claude Opus 4.7
GPT-5.5
Input cost / 1M tokens
$$5.00/1M
$$5.00/1M
Output cost / 1M tokens
$$25.00/1M
$$30.00/1M
Context window
1M tokens
1M tokens
Speed
Deliberate
Balanced
Price tier
Premium
Premium
Benchmarks
SWE-bench (coding)
87.6%
—
Arena Elo
1,800
—
MMLU
92%
—
How they compare
Which model wins for each use case — and why.
Coding ceilingClaude Opus 4.7 wins
Claude Opus 4.7 leads on SWE-Bench Pro at 64.3% vs GPT-5.5 at 58.6%, so it gets the nod for difficult autonomous coding tasks.
OpenAI ecosystemGPT-5.5 wins
GPT-5.5 is the better fit when you need OpenAI APIs, Codex workflows, ChatGPT rollout, or OpenAI-specific agent integrations.
PriceClaude Opus 4.7 wins
Claude Opus 4.7 is listed at $5/$25 per million tokens. GPT-5.5 is $5/$30, so input is tied and Opus has cheaper output.
ContextTie
Both models support a 1M token API context window, so context length is not the deciding factor between them.
Daily agent workflowsTie
Opus 4.7 is the benchmark-first coding choice; GPT-5.5 is the better OpenAI-native agent choice. The right answer depends on where your tooling lives.
Which should you pick?
Pick Claude Opus 4.7 if…
You want the highest current public SWE-Bench Pro coding score
You run premium coding agents, PR review, or high-stakes refactors
You want cheaper output tokens than GPT-5.5 at the same input price
For most workflows, Claude Opus 4.7 is the stronger choice.
Superseded by Opus 4.8 (May 27, 2026) which scores 69.2% SWE-Bench Pro vs 64.3% here — at the same price. For existing pinned integrations Opus 4.7 still works well, but new deployments should use Opus 4.8.
The case for each model
What each one is genuinely good at, where it falls down, and when we would steer you away from it.
Our overall pick in this comparison. Against GPT-5.5 it costs about 14% less per token.
Anthropic's previous Opus flagship, now superseded by Opus 4.8. Still the second-best coding model publicly available at the same $5/$25 price.
Input
$5.00/1M
Output
$25.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Delegating difficult multi-file engineering work that needs careful verification
Running premium coding agents and autonomous PR review workflows
Reading large codebases, research corpora, or design references with 1M context
Where it wins
64.3% on SWE-Bench Pro, ahead of GPT-5.5 and GPT-5.4 in current public comparisons
1M context window for large codebases and document-heavy workflows
Strong vision and agentic consistency improvements over Opus 4.6
Where it falls down
Premium pricing is expensive for high-volume workloads
GPT-5.5 has stronger OpenAI ecosystem fit and faster Codex availability for some teams
Skip it if
You need cheaper high-volume throughput, image generation, or a workflow that must stay inside OpenAI tooling.
Our verdict
Superseded by Opus 4.8 (May 27, 2026) which scores 69.2% SWE-Bench Pro vs 64.3% here — at the same price. For existing pinned integrations Opus 4.7 still works well, but new deployments should use Opus 4.8.
The runner-up here, but not by a wide margin. Against Claude Opus 4.7 it costs about 14% more per token and answers faster.
OpenAI's latest agentic flagship for coding, research, computer-use workflows, and long multi-step knowledge work.
Input
$5.00/1M
Output
$30.00/1M
Context
1M tokens
Speed
Balanced
What people actually use it for
Running multi-file implementation and debugging loops in Codex
Building agents that research, operate tools, and verify work over long tasks
Analyzing large business, scientific, or technical documents with 1M context
Where it wins
58.6% on SWE-Bench Pro, ahead of GPT-5.4 on the same public coding benchmark
82.7% on Terminal-Bench 2.0 for complex command-line workflows
1M token API context window for large-codebase and document-heavy workflows
Where it falls down
Claude Opus 4.7 leads GPT-5.5 on SWE-Bench Pro for pure coding ceiling
Premium API pricing makes it less attractive for high-volume low-risk work
Skip it if
You only care about the highest public coding benchmark score or need a cheaper high-volume model.
Our verdict
The strongest OpenAI pick for agentic coding and knowledge work. Claude Opus 4.7 still wins on the public SWE-Bench Pro coding number, but GPT-5.5 is the better OpenAI default when ecosystem, Codex, or computer-use workflows matter.
Full pricing, benchmark table and release notes on the GPT-5.5 page.
Frequently asked questions
Is Claude Opus 4.7 or GPT-5.5 better for coding?
Claude Opus 4.7 is the better pure coding pick by public SWE-Bench Pro: 64.3% vs GPT-5.5 at 58.6%. GPT-5.5 is still excellent, especially if your workflow is OpenAI/Codex-first.
Is GPT-5.5 cheaper than Claude Opus 4.7?
No. Input pricing is tied at $5 per million tokens, while Claude Opus 4.7 has lower output pricing at $25 per million vs GPT-5.5 at $30 per million.
Which has the larger context window?
Both support a 1M token API context window, so context length is not the deciding factor between them.
When should I choose GPT-5.5 instead?
Choose GPT-5.5 when OpenAI ecosystem fit matters: Codex, ChatGPT, OpenAI APIs, or workflows built around OpenAI agent tooling.