Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Opus 4.6
84
Winner · 1/8 categoriesGLM-5V-Turbo
~58
0/8 categoriesClaude Opus 4.6· GLM-5V-Turbo
Pick Claude Opus 4.6 if you want the stronger benchmark profile. GLM-5V-Turbo only becomes the better choice if you want the cheaper token bill.
Claude Opus 4.6 is clearly ahead on the aggregate, 84 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.6's sharpest advantage is in agentic, where it averages 72.6 against 58. The single biggest benchmark swing on the page is BrowseComp, 84% to 51.9%.
Claude Opus 4.6 is also the more expensive model on tokens at $15.00 input / $75.00 output per 1M tokens, versus $1.20 input / $4.00 output per 1M tokens for GLM-5V-Turbo. That is roughly 18.8x on output cost alone. Claude Opus 4.6 gives you the larger context window at 1M, compared with 200K for GLM-5V-Turbo.
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 | GLM-5V-Turbo |
|---|---|---|
| AgenticClaude Opus 4.6 wins | ||
| Terminal-Bench 2.0 | 65.4% | — |
| BrowseComp | 84% | 51.9% |
| BrowseComp-VL | 35.9% | 51.9% |
| OSWorld | 72.2% | 62.3% |
| Tau2-Airline | 82.0% | — |
| Tau2-Telecom | 92.1% | — |
| PinchBench | 93.3% | — |
| BFCL v4 | 77.0% | — |
| AndroidWorld | 62.0% | 75.7% |
| WebVoyager | 88.0% | 88.5% |
| OSWorld-Verified | — | 62.3% |
| Coding | ||
| SWE-bench Verified | 80.8% | — |
| SWE-bench Verified* | 75.6% | — |
| 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% | 94.8% |
| Flame-VLM-Code | 98.8% | 93.8% |
| Vision2Web | 43.5% | 31.0% |
| MMSearch | 63.8% | 72.9% |
| MMSearch-Plus | 25.6% | 30.0% |
| SimpleVQA | 63.2% | 78.2% |
| V* | 66.5% | 89.0% |
| ImageMining | — | 30.7% |
| Facts-VLM | — | 58.6% |
| 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% | — |
| SuperGPQA | 95% | — |
| MMLU-Pro | 82% | — |
| MMLU-Pro (Arcee) | 89.1% | — |
| HLE | 53% | — |
| FrontierScience | 88% | — |
| SimpleQA | 72% | — |
| Instruction Following | ||
| IFBench | 53.1% | — |
| Multilingual | ||
| MGSM | 96% | — |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| AIME25 (Arcee) | 99.8% | — |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 98% | — |
Claude Opus 4.6 is ahead overall, 84 to 58. The biggest single separator in this matchup is BrowseComp, where the scores are 84% and 51.9%.
Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 72.6 versus 58. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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