Model Comparison
DeepSeek-V4-Flash-Max vs MiMo-V2.5Which is better in 2026?
MiMo-V2.5 significantly outperforms across most benchmarks. DeepSeek-V4-Flash-Max is 1.7x cheaper per token.
Verdict: DeepSeek-V4-Flash-Max vs MiMo-V2.5 — which is better?
DeepSeek-V4-Flash-Max (by DeepSeek) and MiMo-V2.5 (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 0 benchmarks, while MiMo-V2.5 is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.0). MiMo-V2.5 significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-Max is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Flash-Max if…
- cost matters — it's about 1.7x cheaper per token
- you want the most recent training data — it shipped Apr 2026
Choose MiMo-V2.5 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Max outperforms in 0 benchmarks, while MiMo-V2.5 is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.0).
MiMo-V2.5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Max ($0.10/1M tokens) is 1.7x cheaper than MiMo-V2.5 ($0.17/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.20/1M tokens) is 1.7x cheaper than MiMo-V2.5 ($0.34/1M tokens).
In conclusion, MiMo-V2.5 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 has 26.8B more parameters than DeepSeek-V4-Flash-Max, making it 9.4% 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 can generate longer responses up to 131,072 tokens, while DeepSeek-V4-Flash-Max is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
MiMo-V2.5 supports multimodal inputs, whereas DeepSeek-V4-Flash-Max does not.
MiMo-V2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-Max
MiMo-V2.5
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 was released on 2026-04-22.
DeepSeek-V4-Flash-Max is 0 month newer than MiMo-V2.5.
Apr 23, 2026
2 months ago
1d newerApr 22, 2026
2 months ago
Knowledge 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 is available from Novita, DeepInfra.
DeepSeek-V4-Flash-Max
MiMo-V2.5
Outputs Comparison
Key Takeaways
MiMo-V2.5
View detailsXiaomi
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and MiMo-V2.5 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.