MiMo-V2.5
mimo-v2.5MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding... Built by Xiaomi.
Prices updated
Input price
$0.14
per 1M tokens · Standard
Output price
$0.28
per 1M tokens · Standard
Input limit
1.1M
tokens
Output limit
131K
tokens
Input formats
Output formats
MiMo-V2.5 price history
2 price records since 9/25/2026
MiMo-V2.5 cost calculator
$4.20/month
Standard pricing
Overview
What is MiMo-V2.5?
MiMo-V2.5 is a text & reasoning and vision model from Xiaomi. MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding... Its 1.1M context window and $0.14 input price make it a candidate for cost-sensitive, high-throughput applications.
Benchmarks
MiMo-V2.5 benchmarks & speed
How MiMo-V2.5 scores on standardized evaluations, and where it lands among every model we track.
1264
DesignArena Elo
Latency & design
- DesignArena win rate
- 53.6%
- Design battles judged
- 43,253
Independent scores from Artificial Analysis and DesignArena · updated 10/8/2026. Higher is better; ranks compare against every model we track with that score.
Rates
MiMo-V2.5 pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.14
Per 1M tokens
Cached input · Standard
$0.0028
Per 1M tokens
Capabilities
MiMo-V2.5 Tools
Tools available when using MiMo-V2.5 through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Low input cost at $0.14 per million tokens suits high-volume workloads.
- 1.1M context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Real-world cost still depends on prompt length, response length and provider-specific billing rules.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider