Model Comparison

GLM-4.5V vs Qwen3-Coder 480B A35B Instruct

Comparing GLM-4.5V and Qwen3-Coder 480B A35B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-4.5V and Qwen3-Coder 480B A35B Instruct don'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

372.0B diff

Qwen3-Coder 480B A35B Instruct has 372.0B more parameters than GLM-4.5V, making it 344.4% larger.

GLM-4.5V

108.0Bparameters

Qwen3-Coder 480B A35B Instruct

480.0Bparameters

108.0B

GLM-4.5V

480.0B

Qwen3-Coder 480B A35B Instruct

Context Window

Maximum input and output token capacity

Only GLM-4.5V specifies input context (131,072 tokens). Only GLM-4.5V specifies output context (131,072 tokens).

GLM-4.5V

Input131,072 tokens

Output131,072 tokens

Qwen3-Coder 480B A35B Instruct

Input- tokens

Output- tokens

Thu May 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.5V supports multimodal inputs, whereas Qwen3-Coder 480B A35B Instruct does not.

GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5V

Text

Images

Audio

Video

Qwen3-Coder 480B A35B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

GLM-4.5V is licensed under MIT, while Qwen3-Coder 480B A35B Instruct uses Apache 2.0.

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

GLM-4.5V

MIT

Open weights

Qwen3-Coder 480B A35B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5V was released on 2025-08-11, while Qwen3-Coder 480B A35B Instruct was released on 2025-01-31.

GLM-4.5V is 6 months newer than Qwen3-Coder 480B A35B Instruct.

GLM-4.5V

Aug 11, 2025

9 months ago

6mo newer

Qwen3-Coder 480B A35B Instruct

Jan 31, 2025

1.3 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

GLM-4.5V

View details

Zhipu AI

Larger context window (131,072 tokens)

Supports multimodal inputs

Qwen3-Coder 480B A35B Instruct

View details

Alibaba Cloud / Qwen Team

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

Detailed Comparison

AI Model Comparison Table
Feature	GLM-4.5V	Qwen3-Coder 480B A35B Instruct

FAQ

Common questions about GLM-4.5V vs Qwen3-Coder 480B A35B Instruct.

Which is better, GLM-4.5V or Qwen3-Coder 480B A35B Instruct?

GLM-4.5V (Zhipu AI) and Qwen3-Coder 480B A35B 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-4.5V compare to Qwen3-Coder 480B A35B Instruct in benchmarks?

Qwen3-Coder 480B A35B Instruct scores TAU-bench Retail: 77.5%, SWE-Bench Verified: 69.6%, BFCL-v3: 68.7%, Aider-Polyglot: 61.8%, TAU-bench Airline: 60.0%.

What are the context window sizes for GLM-4.5V and Qwen3-Coder 480B A35B Instruct?

GLM-4.5V supports 131K tokens and Qwen3-Coder 480B A35B Instruct 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-4.5V and Qwen3-Coder 480B A35B Instruct?

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

Who makes GLM-4.5V and Qwen3-Coder 480B A35B Instruct?

GLM-4.5V is developed by Zhipu AI and Qwen3-Coder 480B A35B Instruct is developed by Alibaba Cloud / Qwen Team.