Model Comparison
DeepSeek-V4-Flash-Max vs MiMo-V2-ProWhich is better in 2026?
Both models are evenly matched across the benchmarks. DeepSeek-V4-Flash-Max is 12.0x cheaper per token.
Verdict: DeepSeek-V4-Flash-Max vs MiMo-V2-Pro — which is better?
DeepSeek-V4-Flash-Max (by DeepSeek) and MiMo-V2-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 2 benchmarks (SWE-bench Multilingual, SWE-Bench Verified), while MiMo-V2-Pro is better at 2 benchmarks (GDPval-AA, Terminal-Bench 2.0). Both models are evenly matched across the benchmarks.
On price, DeepSeek-V4-Flash-Max is roughly 12.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Max also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Flash-Max if…
- cost matters — it's about 12.0x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
Choose MiMo-V2-Pro if…
- you want predictable pricing at $1.00/M input and $3.00/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Max outperforms in 2 benchmarks (SWE-bench Multilingual, SWE-Bench Verified), while MiMo-V2-Pro is better at 2 benchmarks (GDPval-AA, Terminal-Bench 2.0).
Both models are evenly matched across the 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 10.0x cheaper than MiMo-V2-Pro ($1.00/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.20/1M tokens) is 15.0x cheaper than MiMo-V2-Pro ($3.00/1M tokens).
In conclusion, MiMo-V2-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-Pro has 716.0B more parameters than DeepSeek-V4-Flash-Max, making it 252.1% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to MiMo-V2-Pro's 1,000,000 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 65,536 tokens, while MiMo-V2-Pro is limited to 16,384 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-Max is licensed under MIT, while MiMo-V2-Pro uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Flash-Max was released on 2026-04-23, while MiMo-V2-Pro was released on 2026-03-18.
DeepSeek-V4-Flash-Max is 1 month newer than MiMo-V2-Pro.
Apr 23, 2026
2 months ago
1mo newerMar 18, 2026
4 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-Pro is available from Xiaomi.
DeepSeek-V4-Flash-Max
MiMo-V2-Pro
Outputs Comparison
Key Takeaways
MiMo-V2-Pro
View detailsXiaomi
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and MiMo-V2-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-Pro.