Qwen3.6-35B-A3B leads overall
Ahead on 3 of 3 benchmarks, averaging 10.3 points higher
Summarised from the 3 benchmarks both models were scored on; details in the charts below.

GLM-4.7-Flash
智谱AI
Updates live with the mode filters below.
Best overall
Qwen3.6-35B-A3B · 59.88
Best single
Qwen3.6-35B-A3B · GPQA Diamond 84.85
Modality coverage
Qwen3.6-35B-A3B · 3 modalities
Head to head
3
Benchmarks
0
Wins
3
Losses
-10.28
Average diff
Benchmark-by-benchmark comparison. Changing the thinking mode or tool filters updates the chart and table below.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Each axis is the mean percentage score of one benchmark domain. It is an average, not a capability rating.
Relative edge: none clear / Relative gap: 科学与综合推理 -14.3
Relative edge: 科学与综合推理 +14.3 / Relative gap: none clear
Method: for each model and benchmark, all scores in the current mode scope are averaged (not the best score), then those benchmark scores are averaged within each domain. Only benchmarks scored on a 0-100 scale by at least two of the selected models count — Elo and rating-scale benchmarks such as Codeforces or Arena are excluded, because averaging a 1500 rating with an 85% accuracy produces a meaningless number. Missing values are not counted as zero, and the averages are unweighted, so domains with harder benchmarks read lower.
Every model and runtime mode, benchmark by benchmark. Values are comparable along a row, not between different benchmarks.
3 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | GLM-4.7-Flash | Qwen3.6-35B-A3B |
|---|---|---|
HLE 综合评估 | 14.40Thinking Enabled | 21.40Thinking Enabled |
GPQA Diamond 科学与综合推理 | 75.20Thinking Enabled | 84.85Standard Mode |
SWE-bench Verified 编程与软件工程 | 59.20Thinking Enabled | 73.40Thinking Enabled |
Official list prices per model API, split by input and output. Unit: USD per 1M tokens.
Architecture, licensing and API modalities. "Not provided" means the field is missing from our database.
| Features & specs | GLM-4.7-Flash智谱AI | Qwen3.6-35B-A3B阿里巴巴 |
|---|---|---|
Core specsRelease | 2026-01-19 | 2026-04-16 |
Context length | 200K | 200K |
Total parameters | 31B | 35B |
Active parameters | 3B | 3B |
Max output length | 131,072 tokens | 80,000 tokens |
Architecture | MoE (mixture of experts) | MoE (mixture of experts) |
Runtime modes | 关闭开启 | 关闭开启 |
LicenseCode Open Source | Open Source · MIT License | Open Source · Apache 2.0 |
Weights Open Source | Open Source · MIT License | Open Source · Apache 2.0 |
Licensing status | 免费商用授权 | 免费商用授权 |
Local deploymentWeight size | 62.5GB | Not provided |
VRAM for weights | ≈ 62.5 GB (weights only, excludes KV cache) | Not provided |
Weights | Hugging Face | Hugging Face |
Source repo | GitHub | GitHub |
API modality supportText Input/Output | / | / |
Image Input/Output | Not provided | / |
Video Input/Output | Not provided | / |
ResourcesPaper / report | GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models (related technical report referenced on model card) | Qwen3.6-35B-A3B:智能体编程利器,现已开源 |

Qwen3.6-35B-A3B
阿里巴巴