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DeepSeek-V3.1 vs Mistral Small 3 24B Base

DeepSeek-V3.1 leads the LLM Stats Score 22.3 to -0.3.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek-V3.1 leads the overall LLM Stats Score 22.3 to -0.3, ranking #168 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-V3.1 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-V3.1

  • overall performance matters — it scores 22.3 and ranks #168 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

Choose Mistral Small 3 24B Base

  • you want the most recent training data — it shipped Jan 2025

At a glance

The differences that matter most.

DeepSeek-V3.1
DeepSeek
Mistral Small 3 24B Base
Mistral AI
Core performance indexes
LLM Stats Score
22.3
#168
-0.3
#316
Reasoning
22.6
#161
-0.4
#309
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.27 / M
— / M
Output price
$1.00 / M
— / M
Context window
163,840
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.1
Mistral Small 3 24B Base
Math
18.9#167
4.6#276
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for DeepSeek-V3.1 · 9 for Mistral Small 3 24B Base

2 shared

DeepSeek-V3.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3 24B Base is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

647.4B diff

DeepSeek-V3.1 has 647.4B more parameters than Mistral Small 3 24B Base, making it 2743.2% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Mistral AI
Mistral Small 3 24B Base
23.6Bparameters
671.0B
DeepSeek-V3.1
23.6B
Mistral Small 3 24B Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.1 specifies input context (163,840 tokens). Only DeepSeek-V3.1 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Mistral AI
Mistral Small 3 24B Base
Input- tokens
Output- tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Mistral Small 3 24B Base supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Mistral Small 3 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.1

Text
Images
Audio
Video

Mistral Small 3 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Mistral Small 3 24B Base uses Apache 2.0.

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

DeepSeek-V3.1

MIT

Open weights

Mistral Small 3 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Mistral Small 3 24B Base was released on 2025-01-30.

Mistral Small 3 24B Base is 1 month newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.7 years ago

Mistral Small 3 24B Base

Jan 30, 2025

1.6 years ago

2w newer

Knowledge Cutoff

When training data ends

Mistral Small 3 24B Base has a documented knowledge cutoff of 2023-10-01, while DeepSeek-V3.1's cutoff date is not specified.

We can confirm Mistral Small 3 24B Base's training data extends to 2023-10-01, but cannot make a direct comparison without DeepSeek-V3.1's cutoff date.

DeepSeek-V3.1

—

Mistral Small 3 24B Base

Oct 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.1 and Mistral Small 3 24B Base side-by-side, then vote on the output you prefer.

DeepSeek-V3.1
✓ Preferred
Mistral Small 3 24B Base
Open in Playground

FAQ

Common questions about DeepSeek-V3.1 vs Mistral Small 3 24B Base.

Which is better, DeepSeek-V3.1 or Mistral Small 3 24B Base?

DeepSeek-V3.1 leads the LLM Stats Score 22.3 to -0.3. DeepSeek-V3.1 is made by DeepSeek and Mistral Small 3 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-V3.1 compare to Mistral Small 3 24B Base in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Mistral Small 3 24B Base scores ARC-C: 91.3%, GSM8k: 80.7%, MMLU: 80.7%, TriviaQA: 80.3%, MBPP: 69.6%.

What are the context window sizes for DeepSeek-V3.1 and Mistral Small 3 24B Base?

DeepSeek-V3.1 supports 164K tokens and Mistral Small 3 24B Base 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-V3.1 and Mistral Small 3 24B Base?

Key differences include LLM Stats Score (22.3 vs -0.3), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.1 and Mistral Small 3 24B Base?

DeepSeek-V3.1 is developed by DeepSeek and Mistral Small 3 24B Base is developed by Mistral AI.

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