Model Comparison

DeepSeek-V3 vs Mistral Small 3.1 24B Base

DeepSeek-V3 significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is 3.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Thu Apr 16 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 ($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 ($1.10/1M tokens) is 3.7x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).

In conclusion, DeepSeek-V3 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
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Mistral AI
Mistral Small 3.1 24B Base
Input tokens$0.10
Output tokens$0.30
Best providerMistral
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Model Size

Parameter count comparison

647.0B diff

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

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

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Mistral Small 3.1 24B Base is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Small 3.1 24B Base supports multimodal inputs, whereas DeepSeek-V3 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

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), 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

MIT + Model License (Commercial use allowed)

Open weights

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Mistral Small 3.1 24B Base was released on 2025-03-17.

Mistral Small 3.1 24B Base is 3 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Mistral Small 3.1 24B Base

Mar 17, 2025

1.1 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 is available from DeepSeek. Mistral Small 3.1 24B Base is available from Mistral AI.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

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 (131,072 tokens)
Higher GPQA score (59.1% vs 37.5%)
Higher MMLU score (88.5% vs 81.0%)
Higher MMLU-Pro score (75.9% 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
Mistral AI
Mistral Small 3.1 24B Base

FAQ

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

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 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.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.
Mistral Small 3.1 24B Base is 2.7x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Mistral Small 3.1 24B Base costs $0.10/M input and $0.30/M output via mistral.
DeepSeek-V3 supports 131K 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.
Key differences include context window (131K vs 128K), input pricing ($0.27 vs $0.10/M), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Mistral Small 3.1 24B Base is developed by Mistral AI.