# XiaomiMiMo/MiMo-V2-Flash

MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation Model

Repository: https://github.com/XiaomiMiMo/MiMo-V2-Flash
Canonical: https://ross.abutalabs.com/products/mimo-v2-flash
License: Apache-2.0
License Family: permissive
Last push: 2026-01-08T04:53:37+00:00

## Health v2 (maintenance only)
Score: 43/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 61, release rhythm 35, longevity 18
- inputs: {"age_days": 261, "days_push": 237, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1368, forks 64 (observed 2026-08-28T04:04:31.558155+00:00)

## What it is
MiMo-V2-Flash is a 309B-parameter Mixture-of-Experts language model (15B active) from Xiaomi designed for efficient reasoning, coding, and agentic workflows. It uses a hybrid sliding-window/global attention architecture and Multi-Token Prediction to cut inference costs while supporting 256k context.

## Use cases
- run an efficient open-weight LLM for reasoning tasks
- serve a MoE model with low inference cost
- build coding agents that score well on SWE-Bench
- accelerate LLM rollout generation for RL training
- process long documents with 256k context
- self-host a fast code assistant model

## When to choose
- you need an open Apache-2.0 MoE model balancing reasoning, coding, and agentic performance
- inference cost and output speed matter more than peak quality
- you need very long context with reduced KV-cache memory

## When to avoid
- you need a small model that fits on consumer hardware
- you want a mature ecosystem with broad tooling support
- you need multimodal (image/audio) capabilities

## Facets
- artifact type: learning-resource
- maturity: active
- function: llm-inference, machine-learning, llm-training, agent-framework
- domain: large-language-models, artificial-intelligence, deep-learning
- platform: python, cloud
- tags: mixture-of-experts, reasoning-model, multi-token-prediction, sliding-window-attention, code-generation, agentic-rl, xiaomi, ai-agents, gpu

## Member repositories
- XiaomiMiMo/MiMo-V2-Flash (main) score 43

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:31.558155+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:41:02.309297+00:00, confidence not recorded.
  - readme: https://github.com/XiaomiMiMo/MiMo-V2-Flash (fetched 2026-08-28T04:04:31.558155+00:00, sha 6b60c9a50b0b)
- Data as of 2026-08-30T08:39:29.467469+00:00.