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GLM-4.7 vs Qwen3.6-35B-A3B

GLM-4.7 and Qwen3.6-35B-A3B are closely matched at 34.6 and 32.5 on the LLM Stats Score.

Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

GLM-4.7 and Qwen3.6-35B-A3B are closely matched on the overall LLM Stats Score at 34.6 and 32.5.

The models split the 8 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-4.7

  • you want predictable pricing at $0.60/M input and $2.20/M output

Choose Qwen3.6-35B-A3B

  • you want the most recent training data — it shipped Apr 2026

At a glance

The differences that matter most.

GLM-4.7
Zhipu AI
Qwen3.6-35B-A3B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
34.6
#85
32.5
#97
Reasoning
34.5
#83
33.2
#89
Coding
17.8
#109
20.0
#94
Agents
9.7
#115
11.7
#97
Cost, coverage & limits
Benchmark wins
4 of 8
4 of 8
Input price
$0.60 / M
— / M
Output price
$2.20 / M
— / M
Context window
202,800
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
GLM-4.7
Qwen3.6-35B-A3B
Math
34.7#46
31.2#67
Tool use
8.2#133
11.4#112
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for GLM-4.7 · 49 for Qwen3.6-35B-A3B

8 shared

GLM-4.7 outperforms in 4 benchmarks (Humanity's Last Exam, IMO-AnswerBench, LiveCodeBench v6, SWE-Bench Verified), while Qwen3.6-35B-A3B is better at 4 benchmarks (GPQA, MMLU-Pro, SWE-bench Multilingual, Terminal-Bench 2.0).

Both models are evenly matched across the benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

323.0B diff

GLM-4.7 has 323.0B more parameters than Qwen3.6-35B-A3B, making it 922.9% larger.

Zhipu AI
GLM-4.7
358.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
35.0Bparameters
358.0B
GLM-4.7
35.0B
Qwen3.6-35B-A3B

Context Window

Maximum input and output token capacity

Only GLM-4.7 specifies input context (202,800 tokens). Only GLM-4.7 specifies output context (131,072 tokens).

Zhipu AI
GLM-4.7
Input202,800 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
Input- tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GLM-4.7 and Qwen3.6-35B-A3B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GLM-4.7

Text
Images
Audio
Video

Qwen3.6-35B-A3B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.7 is licensed under MIT, while Qwen3.6-35B-A3B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-4.7

MIT

Open weights

Qwen3.6-35B-A3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.7 was released on 2025-12-22, while Qwen3.6-35B-A3B was released on 2026-04-16.

Qwen3.6-35B-A3B is 4 months newer than GLM-4.7.

GLM-4.7

Dec 22, 2025

8 months ago

Qwen3.6-35B-A3B

Apr 16, 2026

4 months ago

3mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.7 and Qwen3.6-35B-A3B side-by-side, then vote on the output you prefer.

GLM-4.7
✓ Preferred
Qwen3.6-35B-A3B
Open in Playground

FAQ

Common questions about GLM-4.7 vs Qwen3.6-35B-A3B.

Which is better, GLM-4.7 or Qwen3.6-35B-A3B?

GLM-4.7 and Qwen3.6-35B-A3B are closely matched on the LLM Stats Score at 34.6 and 32.5. GLM-4.7 is made by Zhipu AI and Qwen3.6-35B-A3B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.7 compare to Qwen3.6-35B-A3B in benchmarks?

GLM-4.7 scores AIME 2025: 95.7%, Tau-bench: 87.4%, GPQA: 85.7%, LiveCodeBench v6: 84.9%, MMLU-Pro: 84.3%. Qwen3.6-35B-A3B scores MMLU-Redux: 93.3%, MMBench-V1.1: 92.8%, AI2D: 92.7%, AIME 2026: 92.7%, RefCOCO-avg: 92.0%.

What are the context window sizes for GLM-4.7 and Qwen3.6-35B-A3B?

GLM-4.7 supports 203K tokens and Qwen3.6-35B-A3B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.7 and Qwen3.6-35B-A3B?

Key differences include LLM Stats Score (34.6 vs 32.5), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7 and Qwen3.6-35B-A3B?

GLM-4.7 is developed by Zhipu AI and Qwen3.6-35B-A3B is developed by Alibaba Cloud / Qwen Team.

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