Model Comparison

DeepSeek-V2.5 vs Mistral Small 3.1 24B Base

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks. Mistral Small 3.1 24B Base is 1.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V2.5 outperforms in 0 benchmarks, while Mistral Small 3.1 24B Base is better at 1 benchmark (MMLU).

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks.

Wed Apr 22 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-V2.5 ($0.14/1M tokens) is 1.4x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.1x cheaper than Mistral Small 3.1 24B Base ($0.30/1M tokens).

In conclusion, DeepSeek-V2.5 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 Apr 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
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

212.0B diff

DeepSeek-V2.5 has 212.0B more parameters than Mistral Small 3.1 24B Base, making it 883.3% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
236.0B
DeepSeek-V2.5
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

Mistral Small 3.1 24B Base accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Mistral Small 3.1 24B Base can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Small 3.1 24B Base supports multimodal inputs, whereas DeepSeek-V2.5 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-V2.5

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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-V2.5

deepseek

Open weights

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Mistral Small 3.1 24B Base was released on 2025-03-17.

Mistral Small 3.1 24B Base is 10 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Mistral Small 3.1 24B Base

Mar 17, 2025

1.1 years ago

10mo 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-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Mistral Small 3.1 24B Base is available from Mistral AI.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

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
Less expensive output tokens
Mistral AI
Larger context window (128,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher MMLU score (81.0% vs 80.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Mistral AI
Mistral Small 3.1 24B Base

FAQ

Common questions about DeepSeek-V2.5 vs Mistral Small 3.1 24B Base

Mistral Small 3.1 24B Base significantly outperforms across most benchmarks. DeepSeek-V2.5 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-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. 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 1.4x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Mistral Small 3.1 24B Base costs $0.10/M input and $0.30/M output via mistral.
DeepSeek-V2.5 supports 8K 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 (8K vs 128K), input pricing ($0.14 vs $0.10/M), multimodal support (no vs yes), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Mistral Small 3.1 24B Base is developed by Mistral AI.