Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
Winner · 1/8 categoriesKimi K2
53
1/8 categoriesGemma 4 31B· Kimi K2
Pick Gemma 4 31B if you want the stronger benchmark profile. Kimi K2 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B's sharpest advantage is in coding, where it averages 80 against 58.2. The single biggest benchmark swing on the page is LiveCodeBench, 80% to 53.7%. Kimi K2 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B is the reasoning model in the pair, while Kimi K2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemma 4 31B gives you the larger context window at 256K, compared with 128K for Kimi K2.
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 | Gemma 4 31B | Kimi K2 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 47.1% |
| BrowseComp | — | 60.2% |
| Tau2-Telecom | — | 66.1% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | 53.7% |
| SWE-bench Verified | — | 65.8% |
| Multimodal & Grounded | ||
| MMMU-Pro | 76.9% | — |
| Reasoning | ||
| BBH | 74.4% | — |
| MRCRv2 | 66.4% | — |
| hle | — | 44.9% |
| KnowledgeKimi K2 wins | ||
| GPQA | 84.3% | 75.1% |
| MMLU-Pro | 85.2% | 81.1% |
| HLE | 26.5% | — |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 89.5% |
| SuperGPQA | — | 57.2% |
| SimpleQA | — | 31% |
| Instruction Following | ||
| IFEval | — | 89.8% |
| Multilingual | ||
| sweMultilingual | — | 61.1% |
| Mathematics | ||
| AIME 2024 | — | 69.6% |
| AIME 2025 | — | 49.5% |
| MATH-500 | — | 97.4% |
| HMMT Feb 2025 | — | 38.8% |
Gemma 4 31B is ahead overall, 73 to 53. The biggest single separator in this matchup is LiveCodeBench, where the scores are 80% and 53.7%.
Kimi K2 has the edge for knowledge tasks in this comparison, averaging 64 versus 61.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 58.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
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