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MODEL Listed

MiMo-V2.6-Pro-RL

MiMo-V2.6-Pro-RL is a text-generation model from XiaomiMiMo that targets developer workflows rather than general chat. It’s built for coding assistance, documentation, and structured text output, with a focus on integration into existing toolchains via standard APIs. The model supports common tokenization schemes and runs on widely available frameworks, making it approachable for teams already using Hugging Face pipelines or self-hosted inference servers. Compared to heavier proprietary alternatives, it trades some raw scale for faster iteration and clearer licensing — the MIT license means fewer deployment restrictions. Performance-wise, expect solid reasoning on code-related prompts and decent multilingual support, though it may lag behind frontier models on creative or highly open-ended tasks. If you’re building internal dev tools, automating documentation, or need a lightweight assistant for code generation, this is worth testing alongside your current stack. Always check the model card for specific limitations and intended use cases before deploying in production.

XiaomiMiMotext generation
01 / MODEL CARD

Model card

MiMo-V2.6-Pro-RL is a text-generation model from XiaomiMiMo that targets developer workflows rather than general chat. It’s built for coding assistance, documentation, and structured text output, with a focus on integration into existing toolchains via standard APIs. The model supports common tokenization schemes and runs on widely available frameworks, making it approachable for teams already using Hugging Face pipelines or self-hosted inference servers. Compared to heavier proprietary alternatives, it trades some raw scale for faster iteration and clearer licensing — the MIT license means fewer deployment restrictions. Performance-wise, expect solid reasoning on code-related prompts and decent multilingual support, though it may lag behind frontier models on creative or highly open-ended tasks. If you’re building internal dev tools, automating documentation, or need a lightweight assistant for code generation, this is worth testing alongside your current stack. Always check the model card for specific limitations and intended use cases before deploying in production.

Model typetext generation
ProviderXiaomiMiMo
Licensemit
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: XiaomiMiMo/MiMo-V2.6-Pro-RL
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model XiaomiMiMo/MiMo-V2.6-Pro-RL
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model XiaomiMiMo/MiMo-V2.6-Pro-RL README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('XiaomiMiMo/MiMo-V2.6-Pro-RL')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/XiaomiMiMo/MiMo-V2.6-Pro-RL.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/XiaomiMiMo/MiMo-V2.6-Pro-RL.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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