Model Comparison
DeepSeek-V4-Flash-0731 vs MiMo-V2.5-ProWhich is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and MiMo-V2.5-Pro across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs MiMo-V2.5-Pro — which is better?
DeepSeek-V4-Flash-0731 (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.
On price, DeepSeek-V4-Flash-0731 is roughly 4.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Flash-0731 if…
- cost matters — it's about 4.8x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose MiMo-V2.5-Pro if…
- you want predictable pricing at $0.43/M input and $0.87/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and MiMo-V2.5-Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 4.8x cheaper than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 4.8x cheaper than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.5-Pro is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 719.2B more parameters than DeepSeek-V4-Flash-0731, making it 236.6% 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-0731 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-0731 was released on 2026-07-31, while MiMo-V2.5-Pro was released on 2026-04-27.
DeepSeek-V4-Flash-0731 is 3 months newer than MiMo-V2.5-Pro.
Jul 31, 2026
6 days ago
3mo newerApr 27, 2026
3 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-0731 is available from DeepInfra, Fireworks, Novita. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
DeepSeek-V4-Flash-0731
MiMo-V2.5-Pro
Outputs Comparison
Key Takeaways
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 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-0731 vs MiMo-V2.5-Pro.