Model Comparison

DeepSeek-V3 vs Mistral Large 2

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is 6.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (MMLU), while Mistral Large 2 is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Wed Apr 22 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 2 ($2.00/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 5.5x cheaper than Mistral Large 2 ($6.00/1M tokens).

In conclusion, Mistral Large 2 is more expensive than DeepSeek-V3.*

* 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-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Mistral AI
Mistral Large 2
Input tokens$2.00
Output tokens$6.00
Best providerGoogle
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Model Size

Parameter count comparison

548.0B diff

DeepSeek-V3 has 548.0B more parameters than Mistral Large 2, making it 445.5% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Mistral AI
Mistral Large 2
123.0Bparameters
671.0B
DeepSeek-V3
123.0B
Mistral Large 2

Context Window

Maximum input and output token capacity

DeepSeek-V3 accepts 131,072 input tokens compared to Mistral Large 2's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Mistral Large 2 is limited to 128,000 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Mistral AI
Mistral Large 2
Input128,000 tokens
Output128,000 tokens
Wed Apr 22 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Mistral Large 2 uses Mistral Research License.

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 2

Mistral Research License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Mistral Large 2 was released on 2024-07-24.

DeepSeek-V3 is 5 months newer than Mistral Large 2.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

5mo newer
Mistral Large 2

Jul 24, 2024

1.7 years ago

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 2 is available from Google, Mistral AI.

DeepSeek-V3

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

Mistral Large 2

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
* 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 score (88.5% vs 84.0%)
Mistral AI

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Mistral AI
Mistral Large 2

FAQ

Common questions about DeepSeek-V3 vs Mistral Large 2

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Mistral Large 2 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 2 scores GSM8k: 93.0%, HumanEval: 92.0%, MT-Bench: 86.3%, MMLU: 84.0%, MMLU French: 82.8%.
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 2 costs $2.00/M input and $6.00/M output via google.
DeepSeek-V3 supports 131K tokens and Mistral Large 2 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), licensing (MIT + Model License (Commercial use allowed) vs Mistral Research License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Mistral Large 2 is developed by Mistral AI.