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GLM-4.5-Air vs Qwen3 VL 8B Thinking

GLM-4.5-Air leads the LLM Stats Score 24.4 to 16.2.

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

Which is better?

GLM-4.5-Air leads the overall LLM Stats Score 24.4 to 16.2, ranking #164 overall.

In the 3 individual benchmarks reported for both models, GLM-4.5-Air wins 3; 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-4.5-Air

  • overall performance matters — it scores 24.4 and ranks #164 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results

Choose Qwen3 VL 8B Thinking

  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

Core performance indexes
24.4
#164
16.2
#224
23.8
#162
17.2
#211
5.9
#142
4.3
#156
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
— / M
$0.18 / M
Output price
— / M
$2.09 / M
Context window
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
GLM-4.5-Air
Qwen3 VL 8B Thinking
22.5#136
18.8#176
19.6#20
13.7#54
26.6#43
18.4#96
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for GLM-4.5-Air · 50 for Qwen3 VL 8B Thinking

3 shared

GLM-4.5-Air outperforms in 3 benchmarks (BFCL-v3, GPQA, MMLU-Pro), while Qwen3 VL 8B Thinking is better at 0 benchmarks.

GLM-4.5-Air significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

97.0B diff

GLM-4.5-Air has 97.0B more parameters than Qwen3 VL 8B Thinking, making it 1077.8% larger.

Zhipu AI
GLM-4.5-Air
106.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
9.0Bparameters
106.0B
GLM-4.5-Air
9.0B
Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 8B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 8B Thinking specifies output context (262,144 tokens).

Zhipu AI
GLM-4.5-Air
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
Input262,144 tokens
Output262,144 tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 8B Thinking supports multimodal inputs, whereas GLM-4.5-Air does not.

Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5-Air

Text
Images
Audio
Video

Qwen3 VL 8B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5-Air is licensed under MIT, while Qwen3 VL 8B Thinking uses Apache 2.0.

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

GLM-4.5-Air

MIT

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5-Air was released on 2025-07-28, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 2 months newer than GLM-4.5-Air.

GLM-4.5-Air

Jul 28, 2025

1.1 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

12 months ago

1mo 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-4.5-Air and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.

GLM-4.5-Air
✓ Preferred
Qwen3 VL 8B Thinking
Open in Playground

FAQ

Common questions about GLM-4.5-Air vs Qwen3 VL 8B Thinking.

Which is better, GLM-4.5-Air or Qwen3 VL 8B Thinking?

GLM-4.5-Air leads the LLM Stats Score 24.4 to 16.2. GLM-4.5-Air is made by Zhipu AI and Qwen3 VL 8B Thinking 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-4.5-Air compare to Qwen3 VL 8B Thinking in benchmarks?

GLM-4.5-Air scores MATH-500: 98.1%, AIME 2024: 89.4%, MMLU-Pro: 81.4%, TAU-bench Retail: 77.9%, BFCL-v3: 76.4%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

What are the context window sizes for GLM-4.5-Air and Qwen3 VL 8B Thinking?

GLM-4.5-Air supports an unknown number of tokens and Qwen3 VL 8B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.5-Air and Qwen3 VL 8B Thinking?

Key differences include LLM Stats Score (24.4 vs 16.2), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.5-Air and Qwen3 VL 8B Thinking?

GLM-4.5-Air is developed by Zhipu AI and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.