Model Comparison
GLM-5 vs Mistral Medium 3.5Which is better in 2026?
GLM-5 significantly outperforms across most benchmarks. GLM-5 is 1.9x cheaper per token.
Verdict: GLM-5 vs Mistral Medium 3.5 — which is better?
GLM-5 (by Zhipu AI) and Mistral Medium 3.5 (by Mistral AI) 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.
GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while Mistral Medium 3.5 is better at 0 benchmarks. GLM-5 significantly outperforms across most benchmarks.
On price, GLM-5 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Medium 3.5 also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 1.9x cheaper per token
Choose Mistral Medium 3.5 if…
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while Mistral Medium 3.5 is better at 0 benchmarks.
GLM-5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 1.5x cheaper than Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 2.3x cheaper than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Mistral Medium 3.5 is more expensive than GLM-5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5 has 616.0B more parameters than Mistral Medium 3.5, making it 481.3% larger.
Context Window
Maximum input and output token capacity
Mistral Medium 3.5 accepts 256,000 input tokens compared to GLM-5's 200,000 tokens. Mistral Medium 3.5 can generate longer responses up to 256,000 tokens, while GLM-5 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Mistral Medium 3.5 supports multimodal inputs, whereas GLM-5 does not.
Mistral Medium 3.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
Mistral Medium 3.5
License
Usage and distribution terms
GLM-5 is licensed under MIT, while Mistral Medium 3.5 uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Modified MIT License
Open weights
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while Mistral Medium 3.5 was released on 2026-04-29.
Mistral Medium 3.5 is 3 months newer than GLM-5.
Feb 11, 2026
3 months ago
Apr 29, 2026
1 months ago
2mo newerKnowledge 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. Mistral Medium 3.5 is available from Mistral AI.
GLM-5
Mistral Medium 3.5
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
Mistral Medium 3.5
View detailsMistral AI
Detailed Comparison
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FAQ
Common questions about GLM-5 vs Mistral Medium 3.5.