DeepSeek-V4.1-Flash vs Magistral Medium
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 13.1.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 13.1, ranking #12 overall.
In the 2 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 2; this is a narrower head-to-head signal than the composite indexes.
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 #12 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Sep 2026
Choose Magistral Medium
- you are already invested in the Mistral AI ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 6 for Magistral Medium
DeepSeek-V4.1-Flash outperforms in 2 benchmarks (GPQA, Humanity's Last Exam), while Magistral Medium is better at 0 benchmarks.
DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 739.2B more parameters than Magistral Medium, making it 3080.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash and Magistral Medium support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
Magistral Medium
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while Magistral Medium uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while Magistral Medium was released on 2025-06-10.
DeepSeek-V4.1-Flash is 15 months newer than Magistral Medium.
Sep 10, 2026
4 days ago
1.3yr newerJun 10, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
Magistral Medium has a documented knowledge cutoff of 2025-06-01, while DeepSeek-V4.1-Flash's cutoff date is not specified.
We can confirm Magistral Medium's training data extends to 2025-06-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.
—
Jun 2025
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Magistral Medium side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Magistral Medium.