Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
0/8 categoriesQwen3.5-122B-A10B
71
Winner · 4/8 categoriesGemma 4 E4B· Qwen3.5-122B-A10B
Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen3.5-122B-A10B is clearly ahead on the aggregate, 71 to 47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-122B-A10B's sharpest advantage is in reasoning, where it averages 60.2 against 25.4. The single biggest benchmark swing on the page is GPQA, 58.6% to 86.6%.
Qwen3.5-122B-A10B gives you the larger context window at 262K, compared with 128K for Gemma 4 E4B.
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 E4B | Qwen3.5-122B-A10B |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 49.4% |
| BrowseComp | — | 63.8% |
| OSWorld-Verified | — | 58% |
| Tau2-Telecom | — | 79.5% |
| Claw-Eval | — | 47.1% |
| CodingQwen3.5-122B-A10B wins | ||
| LiveCodeBench | 52% | 78.9% |
| SWE-bench Verified | — | 72% |
| Multimodal & GroundedQwen3.5-122B-A10B wins | ||
| MMMU-Pro | 52.6% | 76.9% |
| ReasoningQwen3.5-122B-A10B wins | ||
| BBH | 33.1% | — |
| MRCRv2 | 25.4% | — |
| LongBench v2 | — | 60.2% |
| KnowledgeQwen3.5-122B-A10B wins | ||
| GPQA | 58.6% | 86.6% |
| MMLU-Pro | 69.4% | 86.7% |
| SuperGPQA | — | 67.1% |
| Instruction Following | ||
| IFEval | — | 93.4% |
| Multilingual | ||
| MMLU-ProX | — | 82.2% |
| Mathematics | ||
| Coming soon | ||
Qwen3.5-122B-A10B is ahead overall, 71 to 47. The biggest single separator in this matchup is GPQA, where the scores are 58.6% and 86.6%.
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 65.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 76.3 versus 52. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.5-122B-A10B has the edge for reasoning in this comparison, averaging 60.2 versus 25.4. Gemma 4 E4B stays close enough that the answer can still flip depending on your workload.
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 52.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.