Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5-27B
71
4/8 categoriesQwen3.5 397B (Reasoning)
77
Winner · 3/8 categoriesQwen3.5-27B· Qwen3.5 397B (Reasoning)
Pick Qwen3.5 397B (Reasoning) if you want the stronger benchmark profile. Qwen3.5-27B only becomes the better choice if coding is the priority or you need the larger 262K context window.
Qwen3.5 397B (Reasoning) is clearly ahead on the aggregate, 77 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B (Reasoning)'s sharpest advantage is in agentic, where it averages 74.8 against 51.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 41.6% to 77%. Qwen3.5-27B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Qwen3.5-27B gives you the larger context window at 262K, compared with 128K for Qwen3.5 397B (Reasoning).
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 | Qwen3.5-27B | Qwen3.5 397B (Reasoning) |
|---|---|---|
| AgenticQwen3.5 397B (Reasoning) wins | ||
| Terminal-Bench 2.0 | 41.6% | 77% |
| BrowseComp | 61% | 78% |
| OSWorld-Verified | 56.2% | 70% |
| tau2-bench | 79% | — |
| CodingQwen3.5-27B wins | ||
| SWE-bench Verified | 72.4% | 60% |
| LiveCodeBench | 80.7% | 60% |
| HumanEval | — | 83% |
| SWE-bench Pro | — | 65% |
| SWE-Rebench | — | 59.9% |
| Multimodal & GroundedQwen3.5-27B wins | ||
| MMMU-Pro | 75% | 64% |
| OfficeQA Pro | — | 79% |
| ReasoningQwen3.5 397B (Reasoning) wins | ||
| LongBench v2 | 60.6% | 80% |
| MuSR | — | 85% |
| BBH | — | 91% |
| MRCRv2 | — | 82% |
| KnowledgeQwen3.5-27B wins | ||
| MMLU-Pro | 86.1% | 81% |
| SuperGPQA | 65.6% | 87% |
| GPQA | 85.5% | 89% |
| MMLU | — | 91% |
| HLE | — | 29% |
| FrontierScience | — | 81% |
| SimpleQA | — | 87% |
| Instruction FollowingQwen3.5-27B wins | ||
| IFEval | 95% | 89% |
| MultilingualQwen3.5 397B (Reasoning) wins | ||
| MMLU-ProX | 82.2% | 86% |
| MGSM | — | 91% |
| Mathematics | ||
| AIME 2023 | — | 93% |
| AIME 2024 | — | 95% |
| AIME 2025 | — | 94% |
| HMMT Feb 2023 | — | 89% |
| HMMT Feb 2024 | — | 91% |
| HMMT Feb 2025 | — | 90% |
| BRUMO 2025 | — | 92% |
| MATH-500 | — | 93% |
Qwen3.5 397B (Reasoning) is ahead overall, 77 to 71. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41.6% and 77%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 71.5. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for coding in this comparison, averaging 77.6 versus 61.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for reasoning in this comparison, averaging 82 versus 60.6. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for agentic tasks in this comparison, averaging 74.8 versus 51.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for multimodal and grounded tasks in this comparison, averaging 75 versus 70.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for instruction following in this comparison, averaging 95 versus 89. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for multilingual tasks in this comparison, averaging 87.8 versus 82.2. 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.