Model Comparison

DeepSeek-V3.1 vs Mistral Large 3 (675B Instruct 2512)Which is better in 2026?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 is 1.7x cheaper per token.

Verdict: DeepSeek-V3.1 vs Mistral Large 3 (675B Instruct 2512) — which is better?

DeepSeek-V3.1 (by DeepSeek) and Mistral Large 3 (675B Instruct 2512) (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 3 benchmarks (GPQA, LiveCodeBench, SimpleQA), while Mistral Large 3 (675B Instruct 2512) is better at 0 benchmarks. DeepSeek-V3.1 significantly outperforms across most benchmarks.

On price, DeepSeek-V3.1 is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Mistral Large 3 (675B Instruct 2512) also accepts a larger context window (262,100 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 3 of 3 shared benchmarks
  • cost matters — it's about 1.7x cheaper per token

Choose Mistral Large 3 (675B Instruct 2512) if…

  • you process long inputs — it offers a 262,100 token context window
  • you want the most recent training data — it shipped Dec 2025

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.1 outperforms in 3 benchmarks (GPQA, LiveCodeBench, SimpleQA), while Mistral Large 3 (675B Instruct 2512) is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Wed Jul 29 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.1 costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 1.9x cheaper than Mistral Large 3 (675B Instruct 2512) ($0.50/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 1.5x cheaper than Mistral Large 3 (675B Instruct 2512) ($1.50/1M tokens).

In conclusion, Mistral Large 3 (675B Instruct 2512) is more expensive than DeepSeek-V3.1.*

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

Lowest available price from all providers
Wed Jul 29 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Mistral AI
Mistral Large 3 (675B Instruct 2512)
Input tokens$0.50
Output tokens$1.50
Best providerMistral
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Model Size

Parameter count comparison

4.0B diff

Mistral Large 3 (675B Instruct 2512) has 4.0B more parameters than DeepSeek-V3.1, making it 0.6% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Mistral AI
Mistral Large 3 (675B Instruct 2512)
675.0Bparameters
671.0B
DeepSeek-V3.1
675.0B
Mistral Large 3 (675B Instruct 2512)

Context Window

Maximum input and output token capacity

Mistral Large 3 (675B Instruct 2512) accepts 262,100 input tokens compared to DeepSeek-V3.1's 163,840 tokens. Mistral Large 3 (675B Instruct 2512) can generate longer responses up to 262,100 tokens, while DeepSeek-V3.1 is limited to 163,840 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Mistral AI
Mistral Large 3 (675B Instruct 2512)
Input262,100 tokens
Output262,100 tokens
Wed Jul 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 (675B Instruct 2512) supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Mistral Large 3 (675B Instruct 2512) 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 Large 3 (675B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Mistral Large 3 (675B Instruct 2512) 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 Large 3 (675B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Mistral Large 3 (675B Instruct 2512) was released on 2025-12-04.

Mistral Large 3 (675B Instruct 2512) is 11 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.5 years ago

Mistral Large 3 (675B Instruct 2512)

Dec 4, 2025

7 months 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-V3.1 is available from DeepInfra, Novita. Mistral Large 3 (675B Instruct 2512) 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 Large 3 (675B Instruct 2512)

mistral logo
Mistral
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (74.9% vs 43.9%)
Higher LiveCodeBench score (56.4% vs 34.4%)
Higher SimpleQA score (93.4% vs 23.8%)
Mistral AI
Larger context window (262,100 tokens)
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.1 and Mistral Large 3 (675B Instruct 2512) side-by-side, then vote on the output you prefer.

DeepSeek-V3.1
✓ Preferred
Mistral Large 3 (675B Instruct 2512)
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Mistral AI
Mistral Large 3 (675B Instruct 2512)

FAQ

Common questions about DeepSeek-V3.1 vs Mistral Large 3 (675B Instruct 2512).

Which is better, DeepSeek-V3.1 or Mistral Large 3 (675B Instruct 2512)?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 is made by DeepSeek and Mistral Large 3 (675B Instruct 2512) 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 Large 3 (675B Instruct 2512) in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Mistral Large 3 (675B Instruct 2512) scores MMMLU: 85.5%, AMC_2022_23: 52.0%, GPQA: 43.9%, LiveCodeBench: 34.4%, SimpleQA: 23.8%.

Is DeepSeek-V3.1 cheaper than Mistral Large 3 (675B Instruct 2512)?

DeepSeek-V3.1 is 1.9x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Mistral Large 3 (675B Instruct 2512) costs $0.50/M input and $1.50/M output via mistral.

What are the context window sizes for DeepSeek-V3.1 and Mistral Large 3 (675B Instruct 2512)?

DeepSeek-V3.1 supports 164K tokens and Mistral Large 3 (675B Instruct 2512) supports 262K 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 Large 3 (675B Instruct 2512)?

Key differences include context window (164K vs 262K), input pricing ($0.27 vs $0.50/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 Large 3 (675B Instruct 2512)?

DeepSeek-V3.1 is developed by DeepSeek and Mistral Large 3 (675B Instruct 2512) is developed by Mistral AI.

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