Devstral Small 1.1 vs GPT-4.1 nano
Devstral Small 1.1 leads the LLM Stats Score 9.3 to 1.6. Devstral Small 1.1 is 1.2x cheaper per token.
Mistral AI · OpenAI · Updated for 2026
Which is better?
Devstral Small 1.1 leads the overall LLM Stats Score 9.3 to 1.6, ranking #269 overall.
On price, Devstral Small 1.1 is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 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
- overall performance matters — it scores 9.3 and ranks #269 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.2x cheaper per token
- you want the most recent training data — it shipped Jul 2025
- you need open weights you can self-host or fine-tune
Choose GPT-4.1 nano
- you process long inputs — it offers a 1,047,576 token context window
At a glance
The differences that matter most.
Individual benchmarks
1 reported for Devstral Small 1.1 · 24 for GPT-4.1 nano
Devstral Small 1.1 and GPT-4.1 nanodon'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) costs the same as GPT-4.1 nano ($0.10/1M tokens).
For output processing, Devstral Small 1.1 ($0.30/1M tokens) is 1.3x cheaper than GPT-4.1 nano ($0.40/1M tokens).
In conclusion, GPT-4.1 nano is more expensive than Devstral Small 1.1.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to Devstral Small 1.1's 128,000 tokens. Devstral Small 1.1 can generate longer responses up to 128,000 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4.1 nano supports multimodal inputs, whereas Devstral Small 1.1 does not.
GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
Devstral Small 1.1
GPT-4.1 nano
License
Usage and distribution terms
Devstral Small 1.1 is licensed under Apache 2.0, while GPT-4.1 nano 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 GPT-4.1 nano was released on 2025-04-14.
Devstral Small 1.1 is 3 months newer than GPT-4.1 nano.
Jul 11, 2025
1.2 years ago
2mo newerApr 14, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Devstral Small 1.1's cutoff date is not specified.
We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Devstral Small 1.1's cutoff date.
—
May 2024
Provider Availability
Devstral Small 1.1 is available from Mistral AI. GPT-4.1 nano is available from OpenAI.
Devstral Small 1.1
GPT-4.1 nano
Outputs Comparison
Judge for yourself.
Run your own prompts against Devstral Small 1.1 and GPT-4.1 nano side-by-side, then vote on the output you prefer.
FAQ
Common questions about Devstral Small 1.1 vs GPT-4.1 nano.