DeepSeek-V4.1-Flash vs Devstral Medium
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 13.6. DeepSeek-V4.1-Flash is 2.4x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 13.6, ranking #13 overall.
On price, DeepSeek-V4.1-Flash is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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 DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 2.4x cheaper per token
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
- you need open weights you can self-host or fine-tune
Choose Devstral Medium
- you want predictable pricing at $0.40/M input and $2.00/M output
At a glance
The differences that matter most.
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 1 for Devstral Medium
DeepSeek-V4.1-Flash and Devstral Mediumdon'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, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 1.8x cheaper than Devstral Medium ($0.40/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 3.0x cheaper than Devstral Medium ($2.00/1M tokens).
In conclusion, Devstral Medium is more expensive than DeepSeek-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Devstral Medium's 128,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Devstral Medium is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Devstral Medium does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash
Devstral Medium
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while Devstral Medium uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while Devstral Medium was released on 2025-07-10.
DeepSeek-V4.1-Flash is 14 months newer than Devstral Medium.
Sep 10, 2026
1 weeks ago
1.2yr newerJul 10, 2025
1.2 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
DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Devstral Medium is available from Mistral AI.
DeepSeek-V4.1-Flash
Devstral Medium
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Devstral Medium side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Devstral Medium.