# XueFuzhao/awesome-mixture-of-experts

A collection of AWESOME things about mixture-of-experts

Repository: https://github.com/XueFuzhao/awesome-mixture-of-experts
Canonical: https://ross.abutalabs.com/products/awesome-mixture-of-experts
License Family: other
Last push: 2024-12-08T16:47:31+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1617, "days_push": 633, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1287, forks 89 (observed 2026-08-28T04:04:15.094442+00:00)

## What it is
A curated awesome-list collecting papers, open models, and libraries about Mixture-of-Experts (MoE) architectures in deep learning. It serves as a reading and reference index covering MoE models, systems, and applications.

## Use cases
- find mixture-of-experts papers to read
- learn about MoE architectures for LLMs
- discover open-source MoE models like Mixtral and DeepSeekMoE
- get started with sparse expert models research
- find MoE libraries and implementations
- track recent mixture-of-experts research

## When to choose
- you are researching or learning about mixture-of-experts models
- you want a curated index of MoE papers and open models
- you need a starting point for sparse expert model literature

## When to avoid
- you need runnable MoE training code rather than a reference list
- you want a maintained software library instead of a paper collection

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, llm-training, developer-tools
- domain: deep-learning, large-language-models, machine-learning, tutorials
- platform: cross-platform
- tags: awesome-list, mixture-of-experts, sparse-models, papers, research

## Member repositories
- XueFuzhao/awesome-mixture-of-experts (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:15.094442+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 2026-08-30T04:55:50.631297+00:00, confidence not recorded.
  - readme: https://github.com/XueFuzhao/awesome-mixture-of-experts (fetched 2026-08-28T04:04:15.094442+00:00, sha 7be70c46b730)
- Data as of 2026-08-30T08:39:29.467469+00:00.