lm-sys/fastchat

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

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Summary Information

Updated 14 minutes ago
Added to GitGenius on August 31st, 2026
Created on March 19th, 2023
Open Issues & Pull Requests: 1,041 (+0)
GitHub issues: Enabled
Number of forks: 4,780
Total Stargazers: 39,527 (-1)
Total Subscribers: 356 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 22.2 hours
Mean response time: 41.6 days
90th percentile: 127.5 days
Tracked items: 171

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 95% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 66% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 5% of issues opened in the past year have been closed. Three people close 60% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 205
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 525 days
Stale 30+ days: 194
Stale 90+ days: 175

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (3)
  • good first issue (3)
  • documentation (1)
  • question (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

FastChat is an open platform for training, serving, and evaluating large language model based chatbots.

FastChat addresses the need for a unified system to build, deploy, and benchmark LLM chatbots. It provides training and evaluation code for models like Vicuna and MT-Bench, a distributed multi-model serving system with web UI and OpenAI-compatible REST APIs, and infrastructure for comparative evaluation through side-by-side LLM battles. The platform powers Chatbot Arena, which collects human preference votes to maintain an LLM Elo leaderboard.

Developers should choose FastChat if they need to serve multiple LLMs simultaneously with a unified interface, conduct comparative evaluation of models, or build on established benchmarking infrastructure. It suits projects ranging from research evaluation to production chatbot services. The tool is particularly valuable for teams wanting to replicate or extend Chatbot Arena's evaluation methodology or deploy models like Vicuna that are specifically trained and optimized within this ecosystem.

The project maintains active development with regular releases of new model variants and datasets. It has published technical reports documenting its evaluation methodology and released large-scale conversation datasets for research. The codebase includes comprehensive tooling for both inference and fine-tuning workflows, with support for various context lengths and model architectures. Development activity shows ongoing refinement of the serving infrastructure and expansion of supported models and evaluation benchmarks.