DeepSeek-V4-Pro-0813 vs Mistral Large 3
Comparing DeepSeek-V4-Pro-0813 and Mistral Large 3 across benchmarks, pricing, and capabilities.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Mistral Large 3 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4-Pro-0813 is roughly 5.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- cost matters — it's about 5.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Mistral Large 3
- you want predictable pricing at $2.00/M input and $5.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-0813 and Mistral Large 3don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 4.6x cheaper than Mistral Large 3 ($2.00/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 5.7x cheaper than Mistral Large 3 ($5.00/1M tokens).
In conclusion, Mistral Large 3 is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 925.0B more parameters than Mistral Large 3, making it 137.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Mistral Large 3's 128,000 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Mistral Large 3 is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Mistral Large 3 supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Mistral Large 3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Mistral Large 3
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Mistral Large 3 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Mistral Large 3 was released on 2025-09-01.
DeepSeek-V4-Pro-0813 is 12 months newer than Mistral Large 3.
Aug 13, 2026
1 weeks ago
11mo newerSep 1, 2025
11 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Mistral Large 3 is available from Mistral AI.
DeepSeek-V4-Pro-0813
Mistral Large 3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Mistral Large 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Mistral Large 3.