Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 mini
56
2/8 categoriesQwen3.5-35B-A3B
67
Winner · 5/8 categoriesGPT-4.1 mini· Qwen3.5-35B-A3B
Pick Qwen3.5-35B-A3B if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if reasoning is the priority or you need the larger 1M context window.
Qwen3.5-35B-A3B is clearly ahead on the aggregate, 67 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5-35B-A3B's sharpest advantage is in coding, where it averages 72.6 against 27.6. The single biggest benchmark swing on the page is SWE-bench Verified, 23.6% to 69.2%. GPT-4.1 mini does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B is the reasoning model in the pair, while GPT-4.1 mini 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 262K for Qwen3.5-35B-A3B.
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 | GPT-4.1 mini | Qwen3.5-35B-A3B |
|---|---|---|
| AgenticGPT-4.1 mini wins | ||
| Terminal-Bench 2.0 | 54% | 40.5% |
| BrowseComp | 71% | 61% |
| OSWorld-Verified | 49% | 54.5% |
| tau2-bench | — | 81.2% |
| CodingQwen3.5-35B-A3B wins | ||
| SWE-bench Verified | 23.6% | 69.2% |
| SWE-bench Pro | 30% | — |
| LiveCodeBench | — | 74.6% |
| Multimodal & GroundedQwen3.5-35B-A3B wins | ||
| MMMU-Pro | 66% | 75.1% |
| OfficeQA Pro | 74% | — |
| ReasoningGPT-4.1 mini wins | ||
| LongBench v2 | 80% | 59% |
| MRCRv2 | 82% | — |
| KnowledgeQwen3.5-35B-A3B wins | ||
| MMLU | 87.5% | — |
| GPQA | 64.2% | 84.2% |
| FrontierScience | 61% | — |
| MMLU-Pro | — | 85.3% |
| SuperGPQA | — | 63.4% |
| Instruction FollowingQwen3.5-35B-A3B wins | ||
| IFEval | 88.5% | 91.9% |
| MultilingualQwen3.5-35B-A3B wins | ||
| MMLU-ProX | 72% | 81% |
| Mathematics | ||
| AIME 2024 | 23.1% | — |
Qwen3.5-35B-A3B is ahead overall, 67 to 56. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 69.2%.
Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 79.3 versus 62.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for coding in this comparison, averaging 72.6 versus 27.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for reasoning in this comparison, averaging 80.9 versus 59. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for agentic tasks in this comparison, averaging 56.5 versus 50.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for multimodal and grounded tasks in this comparison, averaging 75.1 versus 69.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for instruction following in this comparison, averaging 91.9 versus 88.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5-35B-A3B has the edge for multilingual tasks in this comparison, averaging 81 versus 72. Inside this category, MMLU-ProX 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.