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GLM-5.3-Flash vs Qwen3.6-35B-A3B

GLM-5.3-Flash leads the LLM Stats Score 51.1 to 32.7.

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

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.1 to 32.7, ranking #12 overall.

In the 5 individual benchmarks reported for both models, GLM-5.3-Flash wins 5; this is a narrower head-to-head signal than the composite indexes.

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

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.1 and ranks #12 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 5 of 5 exact shared results
  • you want the most recent training data — it shipped Aug 2026

Choose Qwen3.6-35B-A3B

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
Qwen3.6-35B-A3B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.1
#12
32.7
#92
Reasoning
49.9
#14
33.4
#86
Coding
36.0
#24
20.1
#89
Agents
37.7
#10
12.0
#93
Cost, coverage & limits
Benchmark wins
5 of 5
0 of 5
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
GLM-5.3-Flash
Qwen3.6-35B-A3B
Vision
31.7#23
23.5#49
Tool use
33.7#3
11.8#103
Multimodal
30.8#25
26.0#38
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for GLM-5.3-Flash · 49 for Qwen3.6-35B-A3B

5 shared

GLM-5.3-Flash outperforms in 5 benchmarks (CharXiv-R, Humanity's Last Exam, MVBench, NL2Repo, Toolathlon), while Qwen3.6-35B-A3B is better at 0 benchmarks.

GLM-5.3-Flash significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

285.0B diff

GLM-5.3-Flash has 285.0B more parameters than Qwen3.6-35B-A3B, making it 814.3% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
35.0Bparameters
320.0B
GLM-5.3-Flash
35.0B
Qwen3.6-35B-A3B

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
Input- tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GLM-5.3-Flash and Qwen3.6-35B-A3B support multimodal inputs.

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

GLM-5.3-Flash

Text
Images
Audio
Video

Qwen3.6-35B-A3B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash 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-5.3-Flash

MIT

Open weights

Qwen3.6-35B-A3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Qwen3.6-35B-A3B was released on 2026-04-16.

GLM-5.3-Flash is 4 months newer than Qwen3.6-35B-A3B.

GLM-5.3-Flash

Aug 26, 2026

5 days ago

4mo newer
Qwen3.6-35B-A3B

Apr 16, 2026

4 months ago

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-5.3-Flash and Qwen3.6-35B-A3B side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Qwen3.6-35B-A3B
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Qwen3.6-35B-A3B.

Which is better, GLM-5.3-Flash or Qwen3.6-35B-A3B?

GLM-5.3-Flash leads the LLM Stats Score 51.1 to 32.7. GLM-5.3-Flash 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-5.3-Flash compare to Qwen3.6-35B-A3B in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. 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-5.3-Flash and Qwen3.6-35B-A3B?

GLM-5.3-Flash supports 1.0M 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-5.3-Flash and Qwen3.6-35B-A3B?

Key differences include LLM Stats Score (51.1 vs 32.7), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and Qwen3.6-35B-A3B?

GLM-5.3-Flash is developed by Zhipu AI and Qwen3.6-35B-A3B is developed by Alibaba Cloud / Qwen Team.

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