Model Comparison

GLM-5 vs QvQ-72B-PreviewWhich is better in 2026?

Comparing GLM-5 and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs QvQ-72B-Preview — which is better?

GLM-5 (by Zhipu AI) and QvQ-72B-Preview (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-5 if…

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

Choose QvQ-72B-Preview if…

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and QvQ-72B-Previewdon'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

670.6B diff

GLM-5 has 670.6B more parameters than QvQ-72B-Preview, making it 913.6% larger.

Zhipu AI
GLM-5
744.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
744.0B
GLM-5
73.4B
QvQ-72B-Preview

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).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Tue Jun 09 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

QvQ-72B-Preview supports multimodal inputs, whereas GLM-5 does not.

QvQ-72B-Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while QvQ-72B-Preview uses Qwen.

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

GLM-5

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while QvQ-72B-Preview was released on 2024-12-25.

GLM-5 is 14 months newer than QvQ-72B-Preview.

GLM-5

Feb 11, 2026

3 months ago

1.1yr newer
QvQ-72B-Preview

Dec 25, 2024

1.5 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

Zhipu AI
Larger context window (200,000 tokens)
Alibaba Cloud / Qwen Team

QvQ-72B-Preview

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Alibaba Cloud / Qwen Team
QvQ-72B-Preview

FAQ

Common questions about GLM-5 vs QvQ-72B-Preview.

Which is better, GLM-5 or QvQ-72B-Preview?

GLM-5 (Zhipu AI) and QvQ-72B-Preview (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-5 compare to QvQ-72B-Preview 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%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for GLM-5 and QvQ-72B-Preview?

GLM-5 supports 200K tokens and QvQ-72B-Preview 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 QvQ-72B-Preview?

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

Who makes GLM-5 and QvQ-72B-Preview?

GLM-5 is developed by Zhipu AI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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