Devstral Small 1.1 vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 45.8 to 8.6. Devstral Small 1.1 is 6.9x cheaper per token.
Mistral AI · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 45.8 to 8.6, ranking #39 overall.
On price, Devstral Small 1.1 is roughly 6.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 4 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Devstral Small 1.1
- cost matters — it's about 6.9x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mistral Large 4
- overall performance matters — it scores 45.8 and ranks #39 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
1 reported for Devstral Small 1.1 · 18 for Mistral Large 4
Devstral Small 1.1 and Mistral Large 4don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Devstral Small 1.1 ($0.10/1M tokens) is 6.8x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, Devstral Small 1.1 ($0.30/1M tokens) is 7.0x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than Devstral Small 1.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1026.0B more parameters than Devstral Small 1.1, making it 4275.0% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to Devstral Small 1.1's 128,000 tokens. Only Devstral Small 1.1 specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas Devstral Small 1.1 does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Devstral Small 1.1
Mistral Large 4
License
Usage and distribution terms
Devstral Small 1.1 is licensed under Apache 2.0, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Devstral Small 1.1 was released on 2025-07-11, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 15 months newer than Devstral Small 1.1.
Jul 11, 2025
1.3 years ago
Oct 6, 2026
1 weeks ago
1.2yr 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. Mistral Large 4 is available from Mistral AI.
Devstral Small 1.1
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Devstral Small 1.1 and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Devstral Small 1.1 vs Mistral Large 4.