OpenMOSS/MOSS

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

12230 stars · 1127 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

MOSS is an open-source tool-augmented conversational large language model from Fudan University, released with base models, SFT models, plugin-augmented variants, quantized checkpoints, and SFT dialogue datasets. The repository provides inference code for local deployment and fine-tuning scripts for adapting the models to custom dialogue data.

Use cases

• run a chatgpt-like conversational model locally
• deploy an open-source LLM on my own GPU
• fine-tune a dialogue model on my own conversation data
• use a language model with plugins like search and text-to-image
• run a quantized LLM on 12GB of VRAM
• download open-source Chinese-English instruction-tuned model weights
• generate code and answers with a self-hosted chatbot

When to choose

• you want a fully open, self-hosted ChatGPT-style model with weights and training data
• you need Chinese-English bilingual dialogue capabilities
• you want to study or reproduce SFT and plugin-augmented LLM training
• you have a single GPU and need int4/int8 quantized inference

When to avoid

• you need state-of-the-art reasoning quality comparable to modern frontier LLMs
• you want a managed API without hosting your own GPU infrastructure
• you need commercial use of the model weights without checking the AGPL-3.0 model license
• you need long-context or multimodal capabilities

Facets

library · maturity maintenance

llm-inference llm-training chatbot nlp large-language-models artificial-intelligence chatbots python conversational-ai tool-augmented-llm quantization sft-data open-source-model fudan-university natural-language-processing gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="OpenMOSS/MOSS")