Compare MiMo-V2.5-Pro from Xiaomi and DeepSeek V4 Pro 0423 from DeepSeek on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the OpenRouter API.


MiMo-V2.5-Pro and DeepSeek V4 Pro 0423 are available through the OpenRouter API, so switching between them takes a model slug change rather than a new integration.
MiMo-V2.5-Pro, from Xiaomi, has a 1,050,000-token context window and is priced at $0.3045/M tokens input, $0.609/M tokens output on OpenRouter.
DeepSeek V4 Pro 0423, from DeepSeek, has a 1,048,576-token context window and is priced at $0.1674/M tokens input, $3.50/M tokens output on OpenRouter.
| Attribute | MiMo-V2.5-Pro | DeepSeek V4 Pro 0423 |
|---|---|---|
| Input price | $0.3045/M tokens | $0.1674/M tokens |
| Output price | $0.609/M tokens | $3.50/M tokens |
| Context window | 1,050,000 tokens | 1,048,576 tokens |
| Intelligence Index | 26.0 | Not available |
| Coding Index | 60.2 | 58.7 |
| Agentic Index | 21.3 | Not available |
| Latency (p50) | 2.60 s | 1.08 s |
| Throughput (p50) | 23.0 tok/s | 83.0 tok/s |
Benchmark data updated
MiMo-V2.5-Pro and DeepSeek V4 Pro 0423 trade off on price: MiMo-V2.5-Pro costs $0.3045/M tokens input and $0.609/M tokens output, while DeepSeek V4 Pro 0423 costs $0.1674/M tokens input and $3.50/M tokens output, so DeepSeek V4 Pro 0423 is cheaper for input tokens and MiMo-V2.5-Pro is cheaper for output tokens.
MiMo-V2.5-Pro has the longer context window at 1,050,000 tokens, compared with 1,048,576 tokens for DeepSeek V4 Pro 0423.
DeepSeek V4 Pro 0423 is faster on OpenRouter, generating a median 83.0 tokens per second compared with 23.0 tokens per second for MiMo-V2.5-Pro.
MiMo-V2.5-Pro scores higher on coding, with an Artificial Analysis Coding Index of 60.2 compared with 58.7 for DeepSeek V4 Pro 0423.