Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3
49
2/8 categoriesGemma 4 26B A4B
64
Winner · 1/8 categoriesDeepSeek V3· Gemma 4 26B A4B
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if reasoning is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 26B A4B is clearly ahead on the aggregate, 64 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 26B A4B's sharpest advantage is in coding, where it averages 77.1 against 39.2. The single biggest benchmark swing on the page is LiveCodeBench, 37.6% to 77.1%. DeepSeek V3 does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
DeepSeek V3 is also the more expensive model on tokens at $0.27 input / $1.10 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 DeepSeek V3 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 26B A4B gives you the larger context window at 256K, compared with 128K for DeepSeek V3.
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 | DeepSeek V3 | Gemma 4 26B A4B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| CodingGemma 4 26B A4B wins | ||
| LiveCodeBench | 37.6% | 77.1% |
| SWE-bench Verified | 42% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 73.8% |
| ReasoningDeepSeek V3 wins | ||
| LongBench v2 | 48.7% | — |
| BBH | — | 64.8% |
| MRCRv2 | — | 44.1% |
| KnowledgeDeepSeek V3 wins | ||
| GPQA | 59.1% | 82.3% |
| MMLU-Pro | 75.9% | 82.6% |
| SimpleQA | 24.9% | — |
| HLE | — | 17.2% |
| HLE w/o tools | — | 8.7% |
| Instruction Following | ||
| IFEval | 86.1% | — |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| AIME 2024 | 39.2% | — |
| MATH-500 | 90.2% | — |
Gemma 4 26B A4B is ahead overall, 64 to 49. The biggest single separator in this matchup is LiveCodeBench, where the scores are 37.6% and 77.1%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 57.5 versus 56.1. 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 39.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
DeepSeek V3 has the edge for reasoning in this comparison, averaging 48.7 versus 44.1. Gemma 4 26B A4B stays close enough that the answer can still flip depending on your workload.
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