Model Comparison

GLM-4.5-Air vs Qwen2.5 VL 72B InstructWhich is better in 2026?

Comparing GLM-4.5-Air and Qwen2.5 VL 72B Instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-4.5-Air vs Qwen2.5 VL 72B Instruct — which is better?

GLM-4.5-Air (by Zhipu AI) and Qwen2.5 VL 72B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose GLM-4.5-Air if…

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

Choose Qwen2.5 VL 72B Instruct if…

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

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-4.5-Air and Qwen2.5 VL 72B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

34.0B diff

GLM-4.5-Air has 34.0B more parameters than Qwen2.5 VL 72B Instruct, making it 47.2% larger.

Zhipu AI
GLM-4.5-Air
106.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
72.0Bparameters
106.0B
GLM-4.5-Air
72.0B
Qwen2.5 VL 72B Instruct

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 72B Instruct supports multimodal inputs, whereas GLM-4.5-Air does not.

Qwen2.5 VL 72B Instruct 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

Qwen2.5 VL 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5-Air is licensed under MIT, while Qwen2.5 VL 72B Instruct uses tongyi-qianwen.

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

GLM-4.5-Air

MIT

Open weights

Qwen2.5 VL 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

GLM-4.5-Air was released on 2025-07-28, while Qwen2.5 VL 72B Instruct was released on 2025-01-26.

GLM-4.5-Air is 6 months newer than Qwen2.5 VL 72B Instruct.

GLM-4.5-Air

Jul 28, 2025

11 months ago

6mo newer
Qwen2.5 VL 72B Instruct

Jan 26, 2025

1.4 years 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

Key Takeaways

No standout differentiators in the data we have for this pair.

Alibaba Cloud / Qwen Team

Qwen2.5 VL 72B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GLM-4.5-Air and Qwen2.5 VL 72B Instruct side-by-side, then vote on the output you prefer.

GLM-4.5-Air
✓ Preferred
Qwen2.5 VL 72B Instruct
Open in Playground
AI Model Comparison Table
Feature
Zhipu AI
GLM-4.5-Air
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct

FAQ

Common questions about GLM-4.5-Air vs Qwen2.5 VL 72B Instruct.

Which is better, GLM-4.5-Air or Qwen2.5 VL 72B Instruct?

GLM-4.5-Air (Zhipu AI) and Qwen2.5 VL 72B Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-4.5-Air compare to Qwen2.5 VL 72B Instruct 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%. Qwen2.5 VL 72B Instruct scores DocVQA: 96.4%, Android Control Low_EM: 93.7%, ChartQA: 89.5%, OCRBench: 88.5%, AI2D: 88.4%.

What are the main differences between GLM-4.5-Air and Qwen2.5 VL 72B Instruct?

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

Who makes GLM-4.5-Air and Qwen2.5 VL 72B Instruct?

GLM-4.5-Air is developed by Zhipu AI and Qwen2.5 VL 72B Instruct is developed by Alibaba Cloud / Qwen Team.