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DeepSeek-V4.1-Flash vs Mistral Small 3.1 24B Base

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 0.3. Mistral Small 3.1 24B Base is 2.2x 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 0.3, ranking #12 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.

On price, Mistral Small 3.1 24B Base is roughly 2.2x 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 #12 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • 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 3.1 24B Base

  • cost matters — it's about 2.2x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Mistral Small 3.1 24B Base
Mistral AI
Core performance indexes
LLM Stats Score
51.8
#12
0.3
#324
Reasoning
48.9
#17
0.5
#315
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.22 / M
$0.10 / M
Output price
$0.66 / M
$0.30 / M
Context window
1,040,000
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Mistral Small 3.1 24B Base
Math
35.2#43
4.7#279
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 5 for Mistral Small 3.1 24B Base

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Mistral Small 3.1 24B Base is better at 0 benchmarks.

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

Fri Sep 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Mistral Small 3.1 24B Base costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 2.2x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 2.2x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).

In conclusion, DeepSeek-V4.1-Flash is more expensive than Mistral Small 3.1 24B Base.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Sep 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Mistral AI
Mistral Small 3.1 24B Base
Input tokens$0.10
Output tokens$0.30
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

739.2B diff

DeepSeek-V4.1-Flash has 739.2B more parameters than Mistral Small 3.1 24B Base, making it 3080.0% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
763.2B
DeepSeek-V4.1-Flash
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Mistral Small 3.1 24B Base is limited to 128,000 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Mistral Small 3.1 24B Base support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Mistral Small 3.1 24B Base 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

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Mistral Small 3.1 24B Base was released on 2025-03-17.

DeepSeek-V4.1-Flash is 18 months newer than Mistral Small 3.1 24B Base.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 days ago

1.5yr newer
Mistral Small 3.1 24B Base

Mar 17, 2025

1.5 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Mistral Small 3.1 24B Base is available from Mistral AI.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Mistral Small 3.1 24B Base

mistral logo
Mistral
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Mistral Small 3.1 24B Base
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Mistral Small 3.1 24B Base.

Which is better, DeepSeek-V4.1-Flash or Mistral Small 3.1 24B Base?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 0.3. DeepSeek-V4.1-Flash is made by DeepSeek and Mistral Small 3.1 24B Base 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 Mistral Small 3.1 24B Base 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%. Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.

Is DeepSeek-V4.1-Flash cheaper than Mistral Small 3.1 24B Base?

Mistral Small 3.1 24B Base is 2.2x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. Mistral Small 3.1 24B Base costs $0.10/M input and $0.30/M output via mistral.

What are the context window sizes for DeepSeek-V4.1-Flash and Mistral Small 3.1 24B Base?

DeepSeek-V4.1-Flash supports 1.0M tokens and Mistral Small 3.1 24B Base supports 128K 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 Mistral Small 3.1 24B Base?

Key differences include LLM Stats Score (51.8 vs 0.3), context window (1.0M vs 128K), input pricing ($0.22 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Mistral Small 3.1 24B Base?

DeepSeek-V4.1-Flash is developed by DeepSeek and Mistral Small 3.1 24B Base is developed by Mistral AI.

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