Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Opus 4.6
84
Winner · 0/8 categoriesTrinity-Large-Thinking
~0
0/8 categoriesClaude Opus 4.6· Trinity-Large-Thinking
Benchmark data for Claude Opus 4.6 and Trinity-Large-Thinking is coming soon on BenchLM.
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Claude Opus 4.6 is priced at $15.00 input / $75.00 output per 1M tokens, versus $0.25 input / $0.90 output per 1M tokens for Trinity-Large-Thinking. Claude Opus 4.6 has the larger context window at 1M, compared with 512K for Trinity-Large-Thinking.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Claude Opus 4.6 | Trinity-Large-Thinking |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 65.4% | — |
| BrowseComp | 84% | — |
| BrowseComp-VL | 35.9% | — |
| OSWorld | 72.2% | — |
| Tau2-Airline | 82.0% | 88.0% |
| Tau2-Telecom | 92.1% | 94.7% |
| PinchBench | 93.3% | 91.9% |
| BFCL v4 | 77.0% | 70.1% |
| AndroidWorld | 62.0% | — |
| WebVoyager | 88.0% | — |
| Coding | ||
| SWE-bench Verified | 80.8% | — |
| SWE-bench Verified* | 75.6% | 63.2% |
| LiveCodeBench | 76% | — |
| FLTEval | 39.6% | — |
| SWE-Rebench | 65.3% | — |
| React Native Evals | 84.4% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 77.3% | — |
| OfficeQA Pro | 94% | — |
| Design2Code | 77.3% | — |
| Flame-VLM-Code | 98.8% | — |
| Vision2Web | 43.5% | — |
| MMSearch | 63.8% | — |
| MMSearch-Plus | 25.6% | — |
| SimpleVQA | 63.2% | — |
| V* | 66.5% | — |
| Reasoning | ||
| MuSR | 93% | — |
| BBH | 94% | — |
| LongBench v2 | 92% | — |
| MRCRv2 | 76% | — |
| ARC-AGI-2 | 68.8% | — |
| Knowledge | ||
| MMLU | 99% | — |
| GPQA | 91.3% | — |
| GPQA-D | 89.2% | 76.3% |
| SuperGPQA | 95% | — |
| MMLU-Pro | 82% | — |
| MMLU-Pro (Arcee) | 89.1% | 83.4% |
| HLE | 53% | — |
| FrontierScience | 88% | — |
| SimpleQA | 72% | — |
| Instruction Following | ||
| IFBench | 53.1% | 52.3% |
| Multilingual | ||
| MGSM | 96% | — |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| AIME25 (Arcee) | 99.8% | 96.3% |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 98% | — |
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
Claude Opus 4.6: $15.00 input / $75.00 output per 1M tokens Trinity-Large-Thinking: $0.25 input / $0.90 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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