Model Comparison
GLM-5 vs Qwen2.5 7B InstructWhich is better in 2026?
Comparing GLM-5 and Qwen2.5 7B Instruct across benchmarks, pricing, and capabilities.
Verdict: GLM-5 vs Qwen2.5 7B Instruct — which is better?
GLM-5 (by Zhipu AI) and Qwen2.5 7B Instruct (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.
On price, Qwen2.5 7B Instruct is roughly 5.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5 if…
- you process long inputs — it offers a 200,000 token context window
- you want the most recent training data — it shipped Feb 2026
Choose Qwen2.5 7B Instruct if…
- cost matters — it's about 5.2x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
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
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
Model Size
Parameter count comparison
GLM-5 has 736.4B more parameters than Qwen2.5 7B Instruct, making it 9676.6% larger.
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.
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.
MIT
Open weights
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.
Feb 11, 2026
3 months ago
1.4yr newerSep 19, 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.
Provider Availability
GLM-5 is available from FriendliAI, ZAI. Qwen2.5 7B Instruct is available from Together.
GLM-5
Qwen2.5 7B Instruct
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
Qwen2.5 7B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about GLM-5 vs Qwen2.5 7B Instruct.