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GLM-5.3-Flash vs QvQ-72B-Preview

Comparing GLM-5.3-Flash and QvQ-72B-Preview across benchmarks, pricing, and capabilities.

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

Which is better?

GLM-5.3-Flash and QvQ-72B-Preview trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

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

Choose QvQ-72B-Preview

  • 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
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,000,000
—
Released
Aug 2026
Dec 2024
License
MIT
Qwen

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash and QvQ-72B-Previewdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

246.6B diff

GLM-5.3-Flash has 246.6B more parameters than QvQ-72B-Preview, making it 336.0% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
320.0B
GLM-5.3-Flash
73.4B
QvQ-72B-Preview

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,000,000 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,000,000 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GLM-5.3-Flash and QvQ-72B-Preview 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

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash 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-5.3-Flash

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while QvQ-72B-Preview was released on 2024-12-25.

GLM-5.3-Flash is 20 months newer than QvQ-72B-Preview.

GLM-5.3-Flash

Aug 26, 2026

0 days ago

1.7yr newer
QvQ-72B-Preview

Dec 25, 2024

1.7 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→

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs QvQ-72B-Preview.

Which is better, GLM-5.3-Flash or QvQ-72B-Preview?

GLM-5.3-Flash (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-5.3-Flash compare to QvQ-72B-Preview in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, MVBench: 77.8%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for GLM-5.3-Flash and QvQ-72B-Preview?

GLM-5.3-Flash supports 1.0M 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-5.3-Flash and QvQ-72B-Preview?

Key differences include licensing (MIT vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and QvQ-72B-Preview?

GLM-5.3-Flash is developed by Zhipu AI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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