DeepSeek-V3 0324 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 13.4. DeepSeek-V3 0324 is 1.3x cheaper per token.
DeepSeek · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 13.4, ranking #19 overall.
On price, DeepSeek-V3 0324 is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Pro 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-V3 0324
- cost matters — it's about 1.3x cheaper per token
Choose MiMo-V2.6-Pro
- overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 18 for MiMo-V2.6-Pro
DeepSeek-V3 0324 and MiMo-V2.6-Prodon'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-V3 0324 ($0.24/1M tokens) is 1.8x cheaper than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, DeepSeek-V3 0324 ($0.90/1M tokens) is 1.0x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.6-Pro is more expensive than DeepSeek-V3 0324.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 349.0B more parameters than DeepSeek-V3 0324, making it 52.0% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to DeepSeek-V3 0324's 163,840 tokens. Only DeepSeek-V3 0324 specifies output context (163,840 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Pro supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
MiMo-V2.6-Pro
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while MiMo-V2.6-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while MiMo-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 18 months newer than DeepSeek-V3 0324.
Mar 25, 2025
1.5 years ago
Sep 22, 2026
0 days ago
1.5yr 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-V3 0324 is available from DeepInfra, Novita. MiMo-V2.6-Pro is available from Xiaomi.
DeepSeek-V3 0324
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs MiMo-V2.6-Pro.