# MiMo V2.5: Self-Hosting Hardware, Scenarios and Commercial License

> Native omnimodal understanding, long-context reasoning and agentic workflows across text, image, video and audio.

- Verified: 2026-09-12
- Released: 2026-04-27
- Canonical: https://chinaapi.ai/open-model-deployment/mimo-v2.5/
- Back to directory: https://chinaapi.ai/open-model-deployment/
- Machine-readable dataset: https://chinaapi.ai/data/open-model-deployment.json

## Model facts

- Vendor: Xiaomi MiMo
- Parameters: 310B total; 15B active
- Native precision: BF16 and FP8 components
- Context: 1M tokens
- Category: General and agentic foundation models
- Modalities: text, image, video, audio → text
- Serving paths: Transformers, SGLang, vLLM
- Official weights: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment
- Model documentation: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment

## Deployment evidence

- **Official launch / minimum — evidence C:** Transformers can load the checkpoint, but the vendor does not state an absolute minimum GPU configuration.
- **200-person team — evidence E:** Use the official distributed recipe as a starting worker and size replicas from the real modality mix.
- **Commercial API — evidence C:** The official card shows an FP8 SGLang DP2×TP8 configuration at 262K context. Source: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment

## Scenario evidence

- **Omnimodal research and support agents — Vendor-stated:** The checkpoint natively accepts text, image, video and audio. Source: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment
- **Long video, audio and document analysis — Vendor-stated:** The model supports up to 1M context and dedicated visual and audio encoders. Source: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment
- **Multimodal tool-using agents — Public evidence:** The official card publishes multimodal, coding, agent and long-context evaluations. Source: https://huggingface.co/XiaomiMiMo/MiMo-V2.5?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment

## Commercial-use check

- License: MIT — https://huggingface.co/XiaomiMiMo/MiMo-V2.5/blob/main/LICENSE?utm_source=chinaapi&utm_medium=research&utm_campaign=open-model-deployment
- MaaS / hosted service: No model-specific MaaS restriction identified in the MIT license.
- Attribution: Retain the copyright and permission notice.

## Avoid or validate first

- Small single-GPU deployment
- Using stale config or tokenizer files from the initial release

## Known limitations and open questions

- Official deployment example is not a minimum
- Audio and video traffic need separate encoder-capacity measurements

## Evidence boundary

Loading weights, completing a first forward pass and meeting a production latency/SLA are separate thresholds. The 200-person and commercial tiers require workload-specific measurement. License summaries are product research, not legal advice.

Generated by GENERATED BY scripts/gen_open_model_deployment.py.