Model Comparison

GLM-5 vs Qwen2.5 7B Instruct

Comparing GLM-5 and Qwen2.5 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 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

Qwen2.5 7B Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 3.3x more expensive than Qwen2.5 7B Instruct ($0.30/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 10.7x more expensive than Qwen2.5 7B Instruct ($0.30/1M tokens).

In conclusion, GLM-5 is more expensive than Qwen2.5 7B Instruct.*

* Using a 3:1 ratio of input to output tokens

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 7B Instruct

Input tokens$0.30

Output tokens$0.30

Best providerTogether

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

736.4B diff

GLM-5 has 736.4B more parameters than Qwen2.5 7B Instruct, making it 9676.6% larger.

GLM-5

744.0Bparameters

Qwen2.5 7B Instruct

7.6Bparameters

744.0B

GLM-5

7.6B

Qwen2.5 7B Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Qwen2.5 7B Instruct's 131,072 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Qwen2.5 7B Instruct is limited to 8,192 tokens.

GLM-5

Input200,000 tokens

Output128,000 tokens

Qwen2.5 7B Instruct

Input131,072 tokens

Output8,192 tokens

Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Qwen2.5 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 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 7B Instruct was released on 2024-09-19.

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

GLM-5

Feb 11, 2026

2 months ago

1.4yr newer

Qwen2.5 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

Provider Availability

GLM-5 is available from ZAI. Qwen2.5 7B Instruct is available from Together.

GLM-5

Unknown Organization

Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Qwen2.5 7B Instruct

Together

Input Price:Input: $0.30/1MOutput Price:Output: $0.30/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

GLM-5

View details

Zhipu AI

Larger context window (200,000 tokens)

Qwen2.5 7B Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

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

FAQ

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

GLM-5 (Zhipu AI) and Qwen2.5 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 7B Instruct scores GSM8k: 91.6%, MT-Bench: 87.5%, HumanEval: 84.8%, MBPP: 79.2%, MATH: 75.5%.

Qwen2.5 7B Instruct is 3.3x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. Qwen2.5 7B Instruct costs $0.30/M input and $0.30/M output via together.

GLM-5 supports 200K tokens and Qwen2.5 7B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include context window (200K vs 131K), input pricing ($1.00 vs $0.30/M), 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 7B Instruct is developed by Alibaba Cloud / Qwen Team.

GLM-5 vs Qwen2.5 7B Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

GLM-5

Qwen2.5 7B Instruct

Outputs Comparison

Key Takeaways

GLM-5

Qwen2.5 7B Instruct

Detailed Comparison

FAQ

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

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

Is GLM-5 cheaper than Qwen2.5 7B Instruct?

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

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

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