Claude Opus 5
Anthropic · Released 24 Jul 2026 · claude-opus-5
$5.00
Input price / 1M tokens
#52 of 61, cheapest first
$25.00
Output price / 1M tokens
#52 of 61, cheapest first
1M
Context window
#29 of 71
55
Output tokens / second
#51 of 61
52.3%
Terminal-Bench 4.0
#6 of 10
48%
FrontierCode 1.1
#3 of 6
26.9%
AutomationBench
#7 of 8
63.6%
Humanity’s Last Exam (with tools)
#6 of 16
Summary
Claude Opus 5 is a proprietary model from Anthropic, released on 24 Jul 2026.
At $5.00 input and $25.00 output per million tokens, it is #52 of 61 on input price, cheapest first.
Its 1M-token context window ranks #29 of 71.
Measured output speed is 55 tokens per second, #51 of 61.
Legacy Opus model, superseded by Claude Opus 5.5. Anthropic described it as coming close to Claude Fable 5's intelligence at half the price, designed for everyday use.
Benchmarks · 10 reported
| Benchmark | Score | Bar | Rank | Source |
|---|---|---|---|---|
| Terminal-Bench 4.0Anthropic setup; public leaderboard (5 trials/task, Claude Code harness) reports 51.8% | 52.3% | #6 of 10 | Anthropic Opus 5.5 launch post (comparison column)Self-reported | |
| FrontierCode 1.1comparison column in a later post | 48% | #3 of 6 | Anthropic Opus 5.5 launch postSelf-reported | |
| CursorBench 4.0comparison column in a later post | 46.6% | – | Anthropic Opus 5.5 launch postSelf-reported | |
| GDPval-AA v2.1comparison column in a later post | 1,708 | Elo-style | – | Anthropic Opus 5.5 launch postSelf-reported |
| AutomationBenchpass rate from Zapier's public leaderboard | 26.9% | #7 of 8 | Zapier public leaderboard, as cited in Anthropic Opus 5.5 launch post | |
| Humanity’s Last Exam (with tools)with tools | 63.6% | #6 of 16 | Anthropic Opus 5.5 launch postSelf-reported | |
| Humanity’s Last Exam (no tools)no tools | 56.6% | #3 of 23 | Anthropic Fable 5.1 / Mythos 5.1 launch post (comparison column)Self-reported | |
| Terminal-Bench-Science 0.1Anthropic setup; public leaderboard (3 trials/task, Claude Code harness) reports 30.0% | 29% | – | Anthropic Opus 5.5 launch postSelf-reported | |
| OSWorld 2.1partial-credit score | 74% | – | Anthropic Opus 5.5 launch postSelf-reported | |
| Chartographywith tools | 83.4% | – | Anthropic Opus 5.5 launch postSelf-reported |
Self-reported means the lab ran the test itself. A rank appears only where several labs report the same version of a benchmark.
Similar models
Models with the most benchmarks in common with Claude Opus 5, and the closest scores.
Terminal-Bench 4.0
#6 of 10Long jobs in a real terminal
- Claude Opus 552.3
- Claude Fable 5.155.8
- Claude Fable 542
- Claude Opus 5.566.4
- Claude Sonnet 5.570.6
- GPT-6 Astra57.9
FrontierCode 1.1
#3 of 6Patches good enough to merge
AutomationBench
#7 of 8End-to-end business workflows
- Claude Opus 526.9
- Claude Fable 5.131.4
- Claude Fable 517.1
- Claude Opus 5.540
- GPT-6 Astra41.4
Humanity’s Last Exam (with tools)
#6 of 16Expert questions, with search and code
- Claude Opus 563.6
- Claude Fable 5.165
- Claude Fable 563.8
- Claude Opus 5.567.7
- Claude Sonnet 5.564.5
- GPT-6 Astra57.2
Compare Claude Opus 5 side by side
Pre-filled with the two closest models. Swap any of them.
Sources
- price, cache prices, batch, fast mode, tokenizer: platform.claude.com/docs/en/about-claude/pricing, checked 2 Oct 2026
- context, max output, release, api id, knowledge cutoff, modalities, min cacheable prompt, legacy status: platform.claude.com/docs/en/models/opus-5/overview, checked 2 Oct 2026
- status, retirement commitment (not sooner than 2027-07-24): platform.claude.com/docs/en/about-claude/model-deprecations, checked 2 Oct 2026
- positioning: anthropic.com/news/claude-opus-5, checked 2 Oct 2026
- benchmarks (comparison columns): anthropic.com/claude-opus-5-5, checked 2 Oct 2026
- benchmarks (comparison columns): anthropic.com/claude-fable-and-mythos-5-1, checked 2 Oct 2026
- output speed: artificialanalysis.ai/models/claude-opus-5, checked 2 Oct 2026
Building on Claude Opus 5?
Get the architecture right before the bill arrives.
We size caching, routing and fallbacks for your workload on a free call, and tell you where a cheaper model is good enough.