Comparative benchmark results across the Qwen3.x model family, covering Coding Agent, General Agent, Search Agent, Knowledge, Instruction Following, Long Context, STEM & Reasoning, and Multilingualism categories.
| Category | Benchmark | Qwen3.5-27B | Qwen3.6-35B-A3B | Qwen3.5-35B-A3B | Qwen3.5-122B-A10B |
|---|---|---|---|---|---|
| Coding Agent | SWE-bench Verified | 75.0 | 73.4 | 69.2 | 72.0 |
| SWE-bench Multilingual | 69.3 | 67.2 | — | — | |
| SWE-bench Pro | 51.2 | 49.5 | — | — | |
| Terminal-Bench 2.0 | 41.6 | 51.5 | 40.5 | 49.4 | |
| Claw-Eval Avg | 64.3 | 68.7 | — | — | |
| Claw-Eval Pass^3 | 46.2 | 50.0 | — | — | |
| SkillsBench Avg | 527.2* | 28.7 | — | — | |
| QwenClawBench | 52.2 | 52.6 | — | — | |
| NL2Repo | 27.3 | 29.4 | — | — | |
| QwenWebBench | 1068 | 1397 | — | — | |
| CodeForces | — | — | 2028 | 2100 | |
| OJBench | — | — | 36.0 | 39.5 | |
| FullStackBench en | — | — | 58.1 | 62.6 | |
| FullStackBench zh | — | — | 55.0 | 58.7 | |
| General Agent | TAU3-Bench | 68.4 | 67.2 | — | — |
| TAU2-Bench | — | — | 81.2 | 79.5 | |
| BFCL-V4 | — | — | 67.3 | 72.2 | |
| VITA-Bench | 41.8 | 35.6 | 31.9 | 33.6 | |
| DeepPlanning | 22.6 | 25.9 | 22.8 | 24.1 | |
| Tool Decathlon | 31.5 | 26.9 | — | — | |
| MCPMark | 36.3 | 37.0 | — | — | |
| MCP-Atlas | 68.4 | 62.8 | — | — | |
| WideSearch | 66.4 | 60.1 | 57.1 | 60.5 | |
| Search Agent | HLE w/ tool | — | — | 47.4 | 47.5 |
| Browsecomp | — | — | 61.0 | 63.8 | |
| Browsecomp-zh | — | — | 69.5 | 69.9 | |
| Seal-0 | — | — | 41.4 | 44.1 | |
| Knowledge | MMLU-Pro | 86.1 | 85.2 | 85.3 | 86.7 |
| MMLU-Redux | 93.2 | 93.3 | 93.3 | 94.0 | |
| SuperGPQA | 65.6 | 64.7 | 63.4 | 67.1 | |
| C-Eval | 90.5 | 90.0 | 90.2 | 91.9 | |
| Instruction Following | IFEval | — | — | 91.9 | 93.4 |
| IFBench | — | — | 70.2 | 76.1 | |
| MultiChallenge | — | — | 60.0 | 61.5 | |
| Long Context | AA-LCR | — | — | 58.5 | 66.9 |
| LongBench v2 | — | — | 59.0 | 60.2 | |
| STEM & Reasoning | GPQA | 85.5 | 86.0 | 84.2 | 86.6 |
| HLE | 24.3 | 21.4 | 22.4 | 25.3 | |
| LiveCodeBench v6 | 80.7 | 80.4 | 74.6 | 78.9 | |
| HMMT Feb 25 | 92.0 | 90.7 | 89.0 | 91.4 | |
| HMMT Nov 25 | 89.8 | 89.1 | 89.2 | 90.3 | |
| HMMT Feb 26 | 84.3 | 83.6 | — | — | |
| IMOAnswerBench | 79.9 | 78.9 | — | — | |
| AIME26 | 92.6 | 92.7 | — | — | |
| Multilingualism | MMMLU | — | — | 85.2 | 86.7 |
| MMLU-ProX | — | — | 81.0 | 82.2 | |
| NOVA-63 | — | — | 57.1 | 58.6 | |
| INCLUDE | — | — | 79.7 | 82.8 | |
| Global PIQA | — | — | 86.6 | 88.4 | |
| PolyMATH | — | — | 64.4 | 68.9 | |
| WMT24++ | — | — | 76.3 | 78.3 | |
| MAXIFE | — | — | 86.6 | 87.9 | |
| Total Wins | 12** | 9 | 1 | 7/29*** |
* The Qwen3.5-27B SkillsBench Avg score of 527.2 is likely not a percentage and appears to be on a fundamentally different scale than the Qwen3.6-35B-A3B score of 28.7 for the same benchmark. This could indicate a raw cumulative score, a scoring methodology change between model releases, or a data entry error in the source table. Treat this figure with caution and verify against the original SkillsBench documentation before using it in any comparative analysis.
** Qwen3.5-27B's win count of 12 excludes the flagged SkillsBench Avg score. Including it brings the total to 13.
*** Qwen3.5-122B-A10B's total win count is 29, but only 7/29 of those wins occur on benchmarks also run by Qwen3.5-27B or Qwen3.6-35B-A3B (MMLU-Pro, MMLU-Redux, SuperGPQA, C-Eval, GPQA, HLE, HMMT Nov 25). The remaining 22 wins come from benchmarks run exclusively against Qwen3.5-35B-A3B — Multilingualism, Search Agent, Instruction Following, and Long Context categories — where there is no cross-model competition. Qwen3.5-35B-A3B's single win (TAU2-Bench) similarly reflects limited benchmark overlap rather than overall underperformance.
Note: — indicates the benchmark was not reported for that model. Wins are only bolded where two or more models share a benchmark.
Deep-dive notes synthesized from research and hands-on testing around Qwen3.6's preserve_thinking feature, dynamic reasoning, and how Qwen's approach compares to Gemma 4:
- Interleaved Thinking — Concepts — What "interleaved thinking" actually means (multimodal vs. reasoning persistence) and why the terminology is confusing.
- Preserve Thinking in Qwen 3.6 — The new
preserve_thinkingflag, KV cache prefix matching, the "two 20-digit numbers" validation test, and a full test matrix from LM Studio. - Toggling Thinking & Sampling Parameters — The difference between
enable_thinkingandpreserve_thinking, plus Alibaba's recommended sampling parameters for each mode (thinking vs. instruct, general vs. coding). - Dynamic Thinking & The Model Router — Autonomous gating, adaptive reasoning latency ("dwelling"), and how tools anchor reasoning budget across model sizes.
- Qwen 3.6 vs. Gemma 4: Two Philosophies — Stateful Persistence (Alibaba) vs. The Clean Slate (Google), failure modes of each, and the "explicit handoff" middle ground.
Thanks to u/onil_gova on r/LocalLLaMA, whose posts kicked off the preserve_thinking investigation that led to the docs in this repo:
- PSA: Qwen3.6 ships with preserve_thinking — make sure it's on
- Qwen3.6 performance jump is real — just make sure…
- Hugging Face: https://huggingface.co/Qwen/Qwen3.5-122B-A10B
- Blog: https://qwen.ai/blog?id=qwen3.5
- License: Apache 2.0
- Released: February 2026
@misc{qwen3.5,
title = {{Qwen3.5}: Towards Native Multimodal Agents},
author = {{Qwen Team}},
month = {February},
year = {2026},
url = {https://qwen.ai/blog?id=qwen3.5}
}- Hugging Face: https://huggingface.co/Qwen/Qwen3.6-35B-A3B
- Blog: https://qwen.ai/blog?id=qwen3.6-35b-a3b
- License: Apache 2.0
- Released: April 2026
@misc{qwen36_35b_a3b,
title = {{Qwen3.6-35B-A3B}: Agentic Coding Power, Now Open to All},
author = {{Qwen Team}},
month = {April},
year = {2026},
url = {https://qwen.ai/blog?id=qwen3.6-35b-a3b}
}