Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.4 Pro
92
Winner · 5/8 categoriesSarvam 105B
60
0/8 categoriesGPT-5.4 Pro· Sarvam 105B
Pick GPT-5.4 Pro if you want the stronger benchmark profile. Sarvam 105B only becomes the better choice if you want the cheaper token bill.
GPT-5.4 Pro is clearly ahead on the aggregate, 92 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 Pro's sharpest advantage is in coding, where it averages 87.2 against 45. The single biggest benchmark swing on the page is SWE-bench Verified, 86% to 45%.
GPT-5.4 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Sarvam 105B. That is roughly Infinityx on output cost alone. GPT-5.4 Pro gives you the larger context window at 1.05M, compared with 128K for Sarvam 105B.
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 | GPT-5.4 Pro | Sarvam 105B |
|---|---|---|
| AgenticGPT-5.4 Pro wins | ||
| Terminal-Bench 2.0 | 90% | — |
| BrowseComp | 89.3% | 49.5% |
| OSWorld-Verified | 84% | — |
| CodingGPT-5.4 Pro wins | ||
| HumanEval | 95% | — |
| SWE-bench Verified | 86% | 45% |
| LiveCodeBench | 86% | — |
| SWE-bench Pro | 89% | — |
| LiveCodeBench v6 | — | 71.7% |
| Multimodal & Grounded | ||
| MMMU-Pro | 94% | — |
| OfficeQA Pro | 96% | — |
| Reasoning | ||
| MuSR | 95% | — |
| BBH | 98% | — |
| LongBench v2 | 95% | — |
| MRCRv2 | 97% | — |
| gpqaDiamond | — | 78.7% |
| hle | — | 11.2% |
| KnowledgeGPT-5.4 Pro wins | ||
| MMLU | 99% | 90.6% |
| GPQA | 99% | — |
| SuperGPQA | 97% | — |
| MMLU-Pro | 94% | 81.7% |
| HLE | 50% | — |
| FrontierScience | 92% | — |
| SimpleQA | 97% | — |
| Instruction FollowingGPT-5.4 Pro wins | ||
| IFEval | 97% | 84.8% |
| Multilingual | ||
| MGSM | 97% | — |
| MMLU-ProX | 95% | — |
| MathematicsGPT-5.4 Pro wins | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 99% | 88.3% |
| HMMT Feb 2023 | 96% | — |
| HMMT Feb 2024 | 98% | — |
| HMMT Feb 2025 | 97% | — |
| BRUMO 2025 | 97% | — |
| MATH-500 | 99% | 98.6% |
| HMMT Feb 2025 | — | 85.8% |
| HMMT Nov 2025 | — | 85.8% |
GPT-5.4 Pro is ahead overall, 92 to 60. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 86% and 45%.
GPT-5.4 Pro has the edge for knowledge tasks in this comparison, averaging 84.9 versus 81.7. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for coding in this comparison, averaging 87.2 versus 45. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for math in this comparison, averaging 98.3 versus 92.3. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for agentic tasks in this comparison, averaging 87.7 versus 49.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for instruction following in this comparison, averaging 97 versus 84.8. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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