Model Comparison

DeepSeek-V3.1 vs Mistral Small 3.1 24B BaseWhich is better in 2026?

DeepSeek-V3.1 significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is 3.0x cheaper per token.

Verdict: DeepSeek-V3.1 vs Mistral Small 3.1 24B Base — which is better?

DeepSeek-V3.1 (by DeepSeek) and Mistral Small 3.1 24B Base (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks. DeepSeek-V3.1 significantly outperforms across most benchmarks.

On price, Mistral Small 3.1 24B Base is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V3.1 also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3.1 if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you process long inputs — it offers a 163,840 token context window

Choose Mistral Small 3.1 24B Base if…

  • cost matters — it's about 3.0x cheaper per token
  • you want the most recent training data — it shipped Mar 2025
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral Small 3.1 24B Base costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 2.7x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 3.3x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).

In conclusion, DeepSeek-V3.1 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
Wed Jun 24 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
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

647.0B diff

DeepSeek-V3.1 has 647.0B more parameters than Mistral Small 3.1 24B Base, making it 2695.8% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
671.0B
DeepSeek-V3.1
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

DeepSeek-V3.1 accepts 163,840 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Mistral Small 3.1 24B Base is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Small 3.1 24B Base supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Mistral Small 3.1 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 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 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-V3.1

MIT

Open weights

Mistral Small 3.1 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 3.1 24B Base was released on 2025-03-17.

Mistral Small 3.1 24B Base is 2 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.5 years ago

Mistral Small 3.1 24B Base

Mar 17, 2025

1.3 years ago

2mo newer

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-V3.1 is available from DeepInfra, Novita. Mistral Small 3.1 24B Base is available from Mistral AI.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

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

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher GPQA score (74.9% vs 37.5%)
Higher MMLU-Pro score (83.7% vs 56.0%)
Mistral AI
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Mistral AI
Mistral Small 3.1 24B Base

FAQ

Common questions about DeepSeek-V3.1 vs Mistral Small 3.1 24B Base.

Which is better, DeepSeek-V3.1 or Mistral Small 3.1 24B Base?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 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 benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.1 compare to Mistral Small 3.1 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 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.

Is DeepSeek-V3.1 cheaper than Mistral Small 3.1 24B Base?

Mistral Small 3.1 24B Base is 2.7x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. 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-V3.1 and Mistral Small 3.1 24B Base?

DeepSeek-V3.1 supports 164K 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-V3.1 and Mistral Small 3.1 24B Base?

Key differences include context window (164K vs 128K), input pricing ($0.27 vs $0.10/M), 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 3.1 24B Base?

DeepSeek-V3.1 is developed by DeepSeek and Mistral Small 3.1 24B Base is developed by Mistral AI.

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