Model Comparison

GLM-5 vs Qwen3.6-35B-A3B

GLM-5 significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GLM-5 outperforms in 3 benchmarks (MCP Atlas, SWE-Bench Verified, Terminal-Bench 2.0), while Qwen3.6-35B-A3B is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

709.0B diff

GLM-5 has 709.0B more parameters than Qwen3.6-35B-A3B, making it 2025.7% larger.

GLM-5

744.0Bparameters

Qwen3.6-35B-A3B

35.0Bparameters

744.0B

GLM-5

35.0B

Qwen3.6-35B-A3B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

GLM-5

Input200,000 tokens

Output128,000 tokens

Qwen3.6-35B-A3B

Input- tokens

Output- tokens

Wed May 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.6-35B-A3B supports multimodal inputs, whereas GLM-5 does not.

Qwen3.6-35B-A3B can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text

Images

Audio

Video

Qwen3.6-35B-A3B

Text

Images

Audio

Video

License

Usage and distribution terms

GLM-5 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-5

MIT

Open weights

Qwen3.6-35B-A3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen3.6-35B-A3B was released on 2026-04-16.

Qwen3.6-35B-A3B is 2 months newer than GLM-5.

GLM-5

Feb 11, 2026

3 months ago

Qwen3.6-35B-A3B

Apr 16, 2026

3 weeks ago

2mo 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→

Key Takeaways

GLM-5

View details

Zhipu AI

Larger context window (200,000 tokens)

Higher MCP Atlas score (67.8% vs 62.8%)

Higher SWE-Bench Verified score (77.8% vs 73.4%)

Higher Terminal-Bench 2.0 score (56.2% vs 51.5%)

Qwen3.6-35B-A3B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature	GLM-5	Qwen3.6-35B-A3B

FAQ

Common questions about GLM-5 vs Qwen3.6-35B-A3B.

Which is better, GLM-5 or Qwen3.6-35B-A3B?

GLM-5 significantly outperforms across most benchmarks. GLM-5 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 benchmark scores, pricing, and capabilities above.

How does GLM-5 compare to Qwen3.6-35B-A3B in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. 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-5 and Qwen3.6-35B-A3B?

GLM-5 supports 200K 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-5 and Qwen3.6-35B-A3B?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Qwen3.6-35B-A3B?

GLM-5 is developed by Zhipu AI and Qwen3.6-35B-A3B is developed by Alibaba Cloud / Qwen Team.