Model Comparison

GLM-5 vs Qwen2.5-Coder 7B Instruct

Comparing GLM-5 and Qwen2.5-Coder 7B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Qwen2.5-Coder 7B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers

Thu Apr 16 2026 • llm-stats.com

GLM-5

Input tokens$1.00

Output tokens$3.20

Best providerUnknown Organization

Qwen2.5-Coder 7B Instruct

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

737.0B diff

GLM-5 has 737.0B more parameters than Qwen2.5-Coder 7B Instruct, making it 10528.6% larger.

GLM-5

744.0Bparameters

Qwen2.5-Coder 7B Instruct

7.0Bparameters

744.0B

GLM-5

7.0B

Qwen2.5-Coder 7B Instruct

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).

GLM-5

Input200,000 tokens

Output128,000 tokens

Qwen2.5-Coder 7B Instruct

Input- tokens

Output- tokens

Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Qwen2.5-Coder 7B Instruct uses Apache 2.0.

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

GLM-5

MIT

Open weights

Qwen2.5-Coder 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen2.5-Coder 7B Instruct was released on 2024-09-19.

GLM-5 is 17 months newer than Qwen2.5-Coder 7B Instruct.

GLM-5

Feb 11, 2026

2 months ago

1.4yr newer

Qwen2.5-Coder 7B Instruct

Sep 19, 2024

1.6 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

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Key Takeaways

GLM-5

View details

Zhipu AI

Larger context window (200,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature	GLM-5	Qwen2.5-Coder 7B Instruct

FAQ

Common questions about GLM-5 vs Qwen2.5-Coder 7B Instruct

GLM-5 (Zhipu AI) and Qwen2.5-Coder 7B 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.

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%. Qwen2.5-Coder 7B Instruct scores HumanEval: 88.4%, GSM8k: 83.9%, MBPP: 83.5%, HellaSwag: 76.8%, Winogrande: 72.9%.

GLM-5 supports 200K tokens and Qwen2.5-Coder 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

GLM-5 is developed by Zhipu AI and Qwen2.5-Coder 7B Instruct is developed by Alibaba Cloud / Qwen Team.

GLM-5 vs Qwen2.5-Coder 7B Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Outputs Comparison

Key Takeaways

GLM-5

Qwen2.5-Coder 7B Instruct

Detailed Comparison

FAQ

Which is better, GLM-5 or Qwen2.5-Coder 7B Instruct?

How does GLM-5 compare to Qwen2.5-Coder 7B Instruct in benchmarks?

What are the context window sizes for GLM-5 and Qwen2.5-Coder 7B Instruct?

What are the main differences between GLM-5 and Qwen2.5-Coder 7B Instruct?

Who makes GLM-5 and Qwen2.5-Coder 7B Instruct?