Model Comparison

DeepSeek-V3 vs Mistral Large 3

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is 5.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (MMLU-Redux), while Mistral Large 3 is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 7.4x cheaper than Mistral Large 3 ($2.00/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 4.5x cheaper than Mistral Large 3 ($5.00/1M tokens).

In conclusion, Mistral Large 3 is more expensive than DeepSeek-V3.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Mistral AI
Mistral Large 3
Input tokens$2.00
Output tokens$5.00
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

4.0B diff

Mistral Large 3 has 4.0B more parameters than DeepSeek-V3, making it 0.6% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Mistral AI
Mistral Large 3
675.0Bparameters
671.0B
DeepSeek-V3
675.0B
Mistral Large 3

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Mistral Large 3's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Mistral Large 3 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral Large 3
Input128,000 tokens
Output8,192 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 supports multimodal inputs, whereas DeepSeek-V3 does not.

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

DeepSeek-V3

Text
Images
Audio
Video

Mistral Large 3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Mistral Large 3 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 Large 3

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Mistral Large 3 was released on 2025-09-01.

Mistral Large 3 is 8 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Mistral Large 3

Sep 1, 2025

7 months ago

8mo 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 Large 3 is available from Mistral AI.

DeepSeek-V3

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

Mistral Large 3

mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $5.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Less expensive input tokens
Less expensive output tokens
Higher MMLU-Redux score (89.1% vs 82.0%)
Mistral AI
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Mistral AI
Mistral Large 3

FAQ

Common questions about DeepSeek-V3 vs Mistral Large 3

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Mistral Large 3 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 Large 3 scores MATH: 90.4%, MM-MT-Bench: 84.9%, MMLU-Redux: 82.0%, TriviaQA: 74.9%, MMMLU: 74.2%.
DeepSeek-V3 is 7.4x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Mistral Large 3 costs $2.00/M input and $5.00/M output via mistral.
DeepSeek-V3 supports 131K tokens and Mistral Large 3 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 $2.00/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 Large 3 is developed by Mistral AI.