DeepSeek R1 Distill Qwen 32B vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 13.1. DeepSeek R1 Distill Qwen 32B is 4.0x cheaper per token.
DeepSeek · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 13.1, ranking #19 overall.
On price, DeepSeek R1 Distill Qwen 32B is roughly 4.0x 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 R1 Distill Qwen 32B
- cost matters — it's about 4.0x 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
4 reported for DeepSeek R1 Distill Qwen 32B · 18 for MiMo-V2.6-Pro
DeepSeek R1 Distill Qwen 32B 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 R1 Distill Qwen 32B ($0.12/1M tokens) is 3.6x cheaper than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 4.8x cheaper than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.6-Pro is more expensive than DeepSeek R1 Distill Qwen 32B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 987.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 3009.8% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to DeepSeek R1 Distill Qwen 32B's 128,000 tokens. Only DeepSeek R1 Distill Qwen 32B specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Pro supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B does not.
MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 32B
MiMo-V2.6-Pro
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while MiMo-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 20 months newer than DeepSeek R1 Distill Qwen 32B.
Jan 20, 2025
1.7 years ago
Sep 22, 2026
-1 days ago
1.7yr 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 R1 Distill Qwen 32B is available from DeepInfra. MiMo-V2.6-Pro is available from Xiaomi.
DeepSeek R1 Distill Qwen 32B
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs MiMo-V2.6-Pro.