DeepSeek-V4.1-Flash vs Mistral Small
Comparing DeepSeek-V4.1-Flash and Mistral Small across benchmarks, pricing, and capabilities.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash and Mistral Small trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Mistral Small is roughly 1.1x 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
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Mistral Small
- cost matters — it's about 1.1x cheaper per token
At a glance
The differences that matter most.
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 0 for Mistral Small
DeepSeek-V4.1-Flash and Mistral Smalldon'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 1.1x more expensive than Mistral Small ($0.20/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.1x more expensive than Mistral Small ($0.60/1M tokens).
In conclusion, DeepSeek-V4.1-Flash is more expensive than Mistral Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 741.2B more parameters than Mistral Small, making it 3369.1% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Mistral Small's 32,768 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Mistral Small is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Mistral Small 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
Mistral Small
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while Mistral Small uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Mistral Research License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while Mistral Small was released on 2024-09-17.
DeepSeek-V4.1-Flash is 24 months newer than Mistral Small.
Sep 10, 2026
1 days ago
2.0yr newerSep 17, 2024
2.0 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. Mistral Small is available from Mistral AI.
DeepSeek-V4.1-Flash
Mistral Small
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Mistral Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Mistral Small.