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DeepSeek-V4.1-Flash vs Magistral Small 2506

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 10.7.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 10.7, ranking #13 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; 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 #13 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose Magistral Small 2506

  • you are already invested in the Mistral AI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Magistral Small 2506
Mistral AI
Core performance indexes
LLM Stats Score
51.8
#13
10.7
#261
Reasoning
48.9
#18
10.9
#259
Coding
44.2
#5
5.2
#201
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Magistral Small 2506
Math
35.2#43
8.5#259
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 4 for Magistral Small 2506

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Magistral Small 2506 is better at 0 benchmarks.

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

739.2B diff

DeepSeek-V4.1-Flash has 739.2B more parameters than Magistral Small 2506, making it 3080.0% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Mistral AI
Magistral Small 2506
24.0Bparameters
763.2B
DeepSeek-V4.1-Flash
24.0B
Magistral Small 2506

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).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Mistral AI
Magistral Small 2506
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas Magistral Small 2506 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

Text
Images
Audio
Video

Magistral Small 2506

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Magistral Small 2506 uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash

MIT

Open weights

Magistral Small 2506

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Magistral Small 2506 was released on 2025-06-10.

DeepSeek-V4.1-Flash is 15 months newer than Magistral Small 2506.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

1.3yr newer
Magistral Small 2506

Jun 10, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while DeepSeek-V4.1-Flash's cutoff date is not specified.

We can confirm Magistral Small 2506's training data extends to 2025-06-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

Magistral Small 2506

Jun 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Magistral Small 2506 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Magistral Small 2506
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Magistral Small 2506.

Which is better, DeepSeek-V4.1-Flash or Magistral Small 2506?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 10.7. DeepSeek-V4.1-Flash is made by DeepSeek and Magistral Small 2506 is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to Magistral Small 2506 in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%.

What are the context window sizes for DeepSeek-V4.1-Flash and Magistral Small 2506?

DeepSeek-V4.1-Flash supports 1.0M tokens and Magistral Small 2506 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash and Magistral Small 2506?

Key differences include LLM Stats Score (51.8 vs 10.7), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Magistral Small 2506?

DeepSeek-V4.1-Flash is developed by DeepSeek and Magistral Small 2506 is developed by Mistral AI.

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