Model Comparison
Devstral Small 1.1 vs GLM-4.6Which is better in 2026?
GLM-4.6 significantly outperforms across most benchmarks. Devstral Small 1.1 is 6.1x cheaper per token.
Verdict: Devstral Small 1.1 vs GLM-4.6 — which is better?
Devstral Small 1.1 (by Mistral AI) and GLM-4.6 (by Zhipu 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.
Devstral Small 1.1 outperforms in 0 benchmarks, while GLM-4.6 is better at 1 benchmark (SWE-Bench Verified). GLM-4.6 significantly outperforms across most benchmarks.
On price, Devstral Small 1.1 is roughly 6.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-4.6 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose Devstral Small 1.1 if…
- cost matters — it's about 6.1x cheaper per token
Choose GLM-4.6 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
Devstral Small 1.1 outperforms in 0 benchmarks, while GLM-4.6 is better at 1 benchmark (SWE-Bench Verified).
GLM-4.6 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Devstral Small 1.1 ($0.10/1M tokens) is 5.5x cheaper than GLM-4.6 ($0.55/1M tokens).
For output processing, Devstral Small 1.1 ($0.30/1M tokens) is 6.7x cheaper than GLM-4.6 ($2.00/1M tokens).
In conclusion, GLM-4.6 is more expensive than Devstral Small 1.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.6 has 333.0B more parameters than Devstral Small 1.1, making it 1387.5% larger.
Context Window
Maximum input and output token capacity
GLM-4.6 accepts 131,072 input tokens compared to Devstral Small 1.1's 128,000 tokens. GLM-4.6 can generate longer responses up to 131,072 tokens, while Devstral Small 1.1 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
GLM-4.6 supports multimodal inputs, whereas Devstral Small 1.1 does not.
GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Devstral Small 1.1
GLM-4.6
License
Usage and distribution terms
Devstral Small 1.1 is licensed under Apache 2.0, while GLM-4.6 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Devstral Small 1.1 was released on 2025-07-11, while GLM-4.6 was released on 2025-09-30.
GLM-4.6 is 3 months newer than Devstral Small 1.1.
Jul 11, 2025
1.0 years ago
Sep 30, 2025
9 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
Devstral Small 1.1 is available from Mistral AI. GLM-4.6 is available from Fireworks, DeepInfra.
Devstral Small 1.1
GLM-4.6
Outputs Comparison
Key Takeaways
Devstral Small 1.1
View detailsMistral AI
GLM-4.6
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Devstral Small 1.1 and GLM-4.6 side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about Devstral Small 1.1 vs GLM-4.6.