DeepSeek-V4-Pro-0813 vs Mistral Large 4
DeepSeek-V4-Pro-0813 and Mistral Large 4 are closely matched at 50.6 and 46.2 on the LLM Stats Score. Mistral Large 4 is 1.6x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Mistral Large 4 are closely matched on the overall LLM Stats Score at 50.6 and 46.2.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Mistral Large 4 is roughly 1.6x 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose Mistral Large 4
- cost matters — it's about 1.6x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 18 for Mistral Large 4
DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (CyberGym), while Mistral Large 4 is better at 1 benchmark (AutomationBench).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($1.30/1M tokens) is 1.9x more expensive than Mistral Large 4 ($0.68/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($2.60/1M tokens) is 1.2x more expensive than Mistral Large 4 ($2.09/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Mistral Large 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 550.0B more parameters than Mistral Large 4, making it 52.4% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Mistral Large 4's 1,000,000 tokens. Only DeepSeek-V4-Pro-0813 specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Mistral Large 4
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 2 months newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
1 months ago
Oct 6, 2026
5 days ago
1mo newerKnowledge 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 DeepInfra, DeepSeek, Novita, Together. Mistral Large 4 is available from Mistral AI.
DeepSeek-V4-Pro-0813
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Mistral Large 4.