Model Comparison
DeepSeek-V4-Pro-Max vs MiMo-V2.5-ProWhich is better in 2026?
DeepSeek-V4-Pro-Max shows notably better performance in the majority of benchmarks. MiMo-V2.5-Pro is 3.7x cheaper per token.
Verdict: DeepSeek-V4-Pro-Max vs MiMo-V2.5-Pro — which is better?
DeepSeek-V4-Pro-Max (by DeepSeek) and MiMo-V2.5-Pro (by Xiaomi) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V4-Pro-Max outperforms in 5 benchmarks (GDPval-AA, GPQA, Humanity's Last Exam, MMLU-Pro, SWE-Bench Verified), while MiMo-V2.5-Pro is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.0). DeepSeek-V4-Pro-Max shows notably better performance in the majority of benchmarks.
On price, MiMo-V2.5-Pro is roughly 3.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Pro-Max if…
- you want the strongest raw capability — it leads on 5 of 7 shared benchmarks
Choose MiMo-V2.5-Pro if…
- cost matters — it's about 3.7x cheaper per token
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-Max outperforms in 5 benchmarks (GDPval-AA, GPQA, Humanity's Last Exam, MMLU-Pro, SWE-Bench Verified), while MiMo-V2.5-Pro is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.0).
DeepSeek-V4-Pro-Max shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-Max ($1.60/1M tokens) is 3.7x more expensive than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($3.20/1M tokens) is 3.7x more expensive than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than MiMo-V2.5-Pro.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 576.8B more parameters than MiMo-V2.5-Pro, making it 56.4% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Both models can generate responses up to 131,072 tokens.
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-V4-Pro-Max was released on 2026-04-23, while MiMo-V2.5-Pro was released on 2026-04-27.
MiMo-V2.5-Pro is 0 month newer than DeepSeek-V4-Pro-Max.
Apr 23, 2026
2 months ago
Apr 27, 2026
2 months ago
4d 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-Max is available from Novita, DeepInfra, DeepSeek, Fireworks, Together. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
DeepSeek-V4-Pro-Max
MiMo-V2.5-Pro
Outputs Comparison
Key Takeaways
DeepSeek-V4-Pro-Max
View detailsDeepSeek
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and MiMo-V2.5-Pro side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Pro-Max vs MiMo-V2.5-Pro.