DeepSeek-V4-Flash-0423 vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 45.8 to 35.9. DeepSeek-V4-Flash-0423 is 9.2x cheaper per token.
DeepSeek · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 45.8 to 35.9, ranking #39 overall.
On price, DeepSeek-V4-Flash-0423 is roughly 9.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0423 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-Flash-0423
- cost matters — it's about 9.2x cheaper per token
- 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
- overall performance matters — it scores 45.8 and ranks #39 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- 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
19 reported for DeepSeek-V4-Flash-0423 · 18 for Mistral Large 4
DeepSeek-V4-Flash-0423 and Mistral Large 4don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0423 ($0.09/1M tokens) is 7.6x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, DeepSeek-V4-Flash-0423 ($0.18/1M tokens) is 11.6x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than DeepSeek-V4-Flash-0423.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 766.0B more parameters than DeepSeek-V4-Flash-0423, making it 269.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0423 accepts 1,048,576 input tokens compared to Mistral Large 4's 1,000,000 tokens. Only DeepSeek-V4-Flash-0423 specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas DeepSeek-V4-Flash-0423 does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0423
Mistral Large 4
License
Usage and distribution terms
DeepSeek-V4-Flash-0423 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-Flash-0423 was released on 2026-04-23, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 6 months newer than DeepSeek-V4-Flash-0423.
Apr 23, 2026
6 months ago
Oct 6, 2026
2 weeks ago
5mo 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-Flash-0423 is available from DeepInfra, Novita. Mistral Large 4 is available from Mistral AI.
DeepSeek-V4-Flash-0423
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0423 and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0423 vs Mistral Large 4.