Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3 Flash
67
Winner · 2/8 categoriesGemma 4 26B A4B
64
2/8 categoriesGemini 3 Flash· Gemma 4 26B A4B
Pick Gemini 3 Flash if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if coding is the priority or you want the cheaper token bill.
Gemini 3 Flash has the cleaner overall profile here, landing at 67 versus 64. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Gemini 3 Flash's sharpest advantage is in reasoning, where it averages 72.7 against 44.1. The single biggest benchmark swing on the page is LiveCodeBench, 36% to 77.1%. Gemma 4 26B A4B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemini 3 Flash is also the more expensive model on tokens at $0.50 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B is the reasoning model in the pair, while Gemini 3 Flash 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 Flash gives you the larger context window at 1M, compared with 256K for Gemma 4 26B A4B.
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 Flash | Gemma 4 26B A4B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 56% | — |
| BrowseComp | 66% | — |
| OSWorld-Verified | 53% | — |
| Claw-Eval | 47.1% | — |
| CodingGemma 4 26B A4B wins | ||
| HumanEval | 62% | — |
| SWE-bench Verified | 44% | — |
| LiveCodeBench | 36% | 77.1% |
| SWE-bench Pro | 44% | — |
| SWE-Rebench | 52.5% | — |
| Multimodal & GroundedGemini 3 Flash wins | ||
| MMMU-Pro | 80% | 73.8% |
| OfficeQA Pro | 79% | — |
| ReasoningGemini 3 Flash wins | ||
| MuSR | 65% | — |
| BBH | 84% | 64.8% |
| LongBench v2 | 75% | — |
| MRCRv2 | 76% | 44.1% |
| KnowledgeGemma 4 26B A4B wins | ||
| MMLU | 70% | — |
| GPQA | 69% | 82.3% |
| SuperGPQA | 67% | — |
| MMLU-Pro | 72% | 82.6% |
| HLE | 6% | 17.2% |
| FrontierScience | 65% | — |
| SimpleQA | 67% | — |
| HLE w/o tools | — | 8.7% |
| Instruction Following | ||
| IFEval | 85% | — |
| Multilingual | ||
| MGSM | 85% | — |
| MMLU-ProX | 78% | — |
| Mathematics | ||
| AIME 2023 | 70% | — |
| AIME 2024 | 72% | — |
| AIME 2025 | 71% | — |
| HMMT Feb 2023 | 66% | — |
| HMMT Feb 2024 | 68% | — |
| HMMT Feb 2025 | 67% | — |
| BRUMO 2025 | 69% | — |
| MATH-500 | 80% | — |
Gemini 3 Flash is ahead overall, 67 to 64. The biggest single separator in this matchup is LiveCodeBench, where the scores are 36% and 77.1%.
Gemma 4 26B A4B has the edge for knowledge tasks in this comparison, averaging 56.1 versus 54. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for coding in this comparison, averaging 77.1 versus 45. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemini 3 Flash has the edge for reasoning in this comparison, averaging 72.7 versus 44.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemini 3 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 73.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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