model: MiMo-V2.6-Flash-RL (mimo2, 309B/15B)
Maintainers usually reply within 1 day
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Active
- Tech stack
- rust
- Domain
- backend, machine-learning
Research direction
Start by comparing the linked Hugging Face config and GGUF files with the existing mimo2 seat implementation and its model loading tests. Check whether the RL file loads with the existing MXFP4 layout and refset identity, then determine whether the separate MTP file needs support. Done means documenting or implementing the required compatibility changes and verifying the model loads; the issue names no source files or tests.
Written by the indexing model from the issue text.
Description
Xiaomi's RL-tuned MiMo-V2.6-Flash, the same family as our mimo2 seat.
- 309B total, 15B active, 1M context, MIT: https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL (created 2026-09-21)
- Its config matches the MOPD file we serve: 48 layers, 256 routed experts, 3 NextN layers: https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL/raw/main/config.json
- 58,264 downloads, 552 likes (read 2026-10-12).
GGUF: https://huggingface.co/ggml-org/MiMo-V2.6-Flash-RL-GGUF (arch mimo2; MXFP4 167 GB, Q2_K 126 GB [derived: shard sum]; separate mtp- and dflash- files).
Reuses: the whole mimo2 seat. Expected new code: none [derived from equal configs].
Open questions:
- Does the RL file load unchanged (MXFP4 layout, refset identity)?
- Does the separate MTP file matter? The seat has no MiMo draft today.
Surveyed with an AI agent; facts link their sources.
- Dominant language
- Rust
- Stars
- 21
- Forks
- 4
- Avg merge
- 2h 32m
- Merged PRs (30d)
- 803
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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