Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3.1 Flash-Lite
56
1/8 categoriesGemma 4 31B
73
Winner · 3/8 categoriesGemini 3.1 Flash-Lite· Gemma 4 31B
Pick Gemma 4 31B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if reasoning is the priority or you need the larger 1M context window.
Gemma 4 31B is clearly ahead on the aggregate, 73 to 56. 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 24.3. The single biggest benchmark swing on the page is LiveCodeBench, 21% to 80%. Gemini 3.1 Flash-Lite does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
Gemini 3.1 Flash-Lite is also the more expensive model on tokens at $0.10 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 31B. That is roughly Infinityx on output cost alone. Gemma 4 31B is the reasoning model in the pair, while Gemini 3.1 Flash-Lite 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. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 256K for Gemma 4 31B.
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 | Gemini 3.1 Flash-Lite | Gemma 4 31B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 47% | — |
| BrowseComp | 60% | — |
| OSWorld-Verified | 44% | — |
| CodingGemma 4 31B wins | ||
| HumanEval | 55% | — |
| SWE-bench Verified | 22% | — |
| LiveCodeBench | 21% | 80% |
| SWE-bench Pro | 29% | — |
| Multimodal & GroundedGemma 4 31B wins | ||
| MMMU-Pro | 74% | 76.9% |
| OfficeQA Pro | 72% | — |
| ReasoningGemini 3.1 Flash-Lite wins | ||
| MuSR | 58% | — |
| BBH | 74% | 74.4% |
| LongBench v2 | 69% | — |
| MRCRv2 | 73% | 66.4% |
| KnowledgeGemma 4 31B wins | ||
| MMLU | 63% | — |
| GPQA | 62% | 84.3% |
| SuperGPQA | 60% | — |
| MMLU-Pro | 63% | 85.2% |
| HLE | 1% | 26.5% |
| FrontierScience | 55% | — |
| SimpleQA | 60% | — |
| HLE w/o tools | — | 19.5% |
| Instruction Following | ||
| IFEval | 79% | — |
| Multilingual | ||
| MGSM | 73% | — |
| MMLU-ProX | 68% | — |
| Mathematics | ||
| AIME 2023 | 63% | — |
| AIME 2024 | 65% | — |
| AIME 2025 | 64% | — |
| HMMT Feb 2023 | 59% | — |
| HMMT Feb 2024 | 61% | — |
| HMMT Feb 2025 | 60% | — |
| BRUMO 2025 | 62% | — |
| MATH-500 | 71% | — |
Gemma 4 31B is ahead overall, 73 to 56. The biggest single separator in this matchup is LiveCodeBench, where the scores are 21% and 80%.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 46.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 24.3. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemini 3.1 Flash-Lite has the edge for reasoning in this comparison, averaging 67.4 versus 66.4. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 73.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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