Claude Opus 4.1 (batch)
Anthropic · released Aug 5, 2025
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
Specification
- Context window
- 200K
- Max output
- 32K
- Knowledge cutoff
- Jan 31, 2025
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- Yes
Intelligence
28.8
72th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
—
Median across providers
Latency
—
Time to first token
Cost per task
$3.38
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
This model has not been put through the benchmark suite. Its speed, latency and pricing figures below are still measured.
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Step 3.7 FlashStepFun30.9
- Mistral Medium 3.5Mistral AI30.4
- Qwen3.5-35B-A3BQwen29.9
- Claude Sonnet 4.5Anthropic29.9
- MiniMax M2MiniMax28.9
- Claude Opus 4.1 (batch)Anthropic28.8
- Claude Opus 4.1Anthropic28.8
- Ling-2.6-1TInclusionAI26.6
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Step 3.7 Flash | 30.9 |
| Mistral Medium 3.5 | 30.4 |
| Qwen3.5-35B-A3B | 29.9 |
| Claude Sonnet 4.5 | 29.9 |
| MiniMax M2 | 28.9 |
| Claude Opus 4.1 (batch) | 28.8 |
| Claude Opus 4.1 | 28.8 |
| Ling-2.6-1T | 26.6 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $7.5
- Output / 1M tokens
- $37.5
- Cached input / 1M
- $0.75
- Blended 3:1
- $15
One task, estimated
$3.38
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.