Anthropic, released Aug 5, 2025
Claude Opus 4.1price, context, benchmarks and release details
Provisional: not enough results to rank yet 80% confidence 80 percent, High confidence, 3 of 7 expected sources in
51.5
SI Score
#102 of 142 ranked models
- Input, per 1M tokens
- not yet reported
- Output, per 1M tokens
- not yet reported
- Context window
- 200Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 32Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Aug 5, 2025models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
How the score breaks down
Coding (weight 40 percent) 73.3
Math (weight 15 percent) 17.6
Preference (weight 15 percent) 74.9
Reasoning (weight 30 percent) 30.5
Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.
Around it on the leaderboard
- 100 GPT OSS 20B 52.5
- 101 Claude Sonnet 3.5 v2 51.9
- 102 Claude Opus 4.1 51.5
- 103 o4-mini 51.2
- 104 Llama 4 Scout 17B Instruct 51.0
Benchmark results
7 benchmarks, 11 resultsEach row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.
GPQA Diamondreasoning 77.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 16KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
77.3 3 settings
- 16K thinking 77.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 16KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - 27K thinking 76.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 27KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 3 73.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
Humanity's Last Exam (Scale AI)reasoning 7.9%Humanity’s Last ExamPotential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions. [variant] Published Aug 8, 2025
Retrieved Oct 9, 2026 · factual citation
Open source ↗ 7.9
Open source ↗ 7.9
FrontierMath Tier 4 (v2)math 2.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Jun 11, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 2.4
Open source ↗ 2.4
FrontierMath Tiers 1–3 (v2)math 12.6%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Jun 11, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 12.6
Open source ↗ 12.6
OTIS Mock AIME 2024–2025math 68.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 27KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
68.9 3 settings
- 16K thinking 64.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 16KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - 27K thinking 68.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 27KPublished Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 3 40%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 5, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
SWE-bench Verifiedcoding 73.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 11, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 73.3
Open source ↗ 73.3
LMArena Textpreference 1418.6 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 74.9
Open source ↗ 74.9
Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.
Details and sources
- Open weights
- Nomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, image, pdfmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 64% of expected source weight
Reported (3)
- Epoch AI BenchmarkingOct 8, 2026
- Humanity’s Last ExamOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (4)
- ARC Prize13% of weight
- Official model cards via models.dev4% of weight
- LiveBench13% of weight
- Terminal-Bench6% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.