Model Comparison
DeepSeek-V4-Flash-Max vs MiMo-V2.5-ProWhich is better in 2026?
DeepSeek-V4-Flash-Max has a slight edge in benchmark performance. DeepSeek-V4-Flash-Max is 4.3x cheaper per token.
Verdict: DeepSeek-V4-Flash-Max vs MiMo-V2.5-Pro — which is better?
DeepSeek-V4-Flash-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-Flash-Max outperforms in 4 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro, SWE-Bench Verified), while MiMo-V2.5-Pro is better at 3 benchmarks (GDPval-AA, SWE-Bench Pro, Terminal-Bench 2.0). DeepSeek-V4-Flash-Max has a slight edge in benchmark performance.
On price, DeepSeek-V4-Flash-Max is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Flash-Max if…
- you want the strongest raw capability — it leads on 4 of 7 shared benchmarks
- cost matters — it's about 4.3x cheaper per token
Choose MiMo-V2.5-Pro if…
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Max outperforms in 4 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro, SWE-Bench Verified), while MiMo-V2.5-Pro is better at 3 benchmarks (GDPval-AA, SWE-Bench Pro, Terminal-Bench 2.0).
DeepSeek-V4-Flash-Max has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Max ($0.10/1M tokens) is 4.3x cheaper than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.20/1M tokens) is 4.3x cheaper than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.5-Pro is more expensive than DeepSeek-V4-Flash-Max.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 739.2B more parameters than DeepSeek-V4-Flash-Max, making it 260.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. MiMo-V2.5-Pro can generate longer responses up to 131,072 tokens, while DeepSeek-V4-Flash-Max is limited to 65,536 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-Flash-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-Flash-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-Flash-Max is available from DeepInfra, DeepSeek, Fireworks, Novita. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
DeepSeek-V4-Flash-Max
MiMo-V2.5-Pro
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-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-Flash-Max vs MiMo-V2.5-Pro.