8 Best FastChat Alternatives in 2026 (Open Source)
FastChat — An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena. Powers Chatbot Arena (lmarena.ai) with 10M+ chat requests and 1.5M+ human votes — the de facto platform for LLM evaluation via crowdsourced human preference, plus an OpenAI-compatible serving layer for 70+ models
Short answer
- Closest match to FastChat: Text Generation Inference.
- Most actively developed: vLLM (3,946 commits in the last 90 days).
- Fastest growing: llama.cpp (+4,859 GitHub stars in the last 30 days).
- No commit in 6+ months: Text Generation Inference, OpenChat and Chatbot UI.
These 8 open-source tools do the same job. They are ordered by how closely they match FastChat, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| FastChat(original) | 39.6k | +16 | 2025-06-02 |
| Text Generation Inference | 10.9k | +11 | 2026-03-21 |
| vLLM | 93.0k | +2,951 | 2026-10-01 |
| llama.cpp | 130.0k | +4,859 | 2026-10-01 |
| llama-cpp-python | 10.6k | +85 | 2026-10-01 |
| TextGen | 47.7k | +216 | 2026-08-17 |
| Chat UI | 11.0k | +57 | 2026-09-30 |
| OpenChat | 5.2k | -5 | 2024-02-27 |
| Chatbot UI | 33.3k | +34 | 2024-06-22 |
1. Text Generation Inference
Large Language Model Text Generation Inference
What sets it apart: Battle-tested in production at Hugging Face (powers HuggingChat and Inference API) — now in maintenance mode with recommendation to use vLLM/SGLang, but remains the reference implementation for optimized LLM serving with the broadest hardware support
Best for: Production LLM serving with HuggingFace models at scale; Teams needing OpenAI-compatible API for open-source models
2. vLLM
A high-throughput and memory-efficient inference and serving engine for LLMs
What sets it apart: Unlike llama.cpp (consumer-hardware focused, C++ native), vLLM is the production throughput king with PagedAttention achieving 2-24x higher throughput than HuggingFace Transformers on datacenter GPUs
Best for: Production LLM serving requiring maximum throughput with PagedAttention and continuous batching; Teams serving multiple LoRA adapters from a single base model in production
3. llama.cpp
LLM inference in C/C++
What sets it apart: Unlike vLLM (optimized for datacenter throughput), llama.cpp targets maximum hardware compatibility from Raspberry Pi to multi-GPU servers with the widest quantization range (1.5-bit to 8-bit)
Best for: Running LLMs on consumer hardware with aggressive quantization (1.5-bit to 8-bit); Deploying OpenAI-compatible local API servers on edge devices or laptops
4. llama-cpp-python
Python bindings for llama.cpp
What sets it apart: vs vLLM: optimized for local/edge deployment with GGUF quantized models on consumer hardware; vs Ollama: programmatic Python API with LangChain/LlamaIndex integration rather than CLI-first approach
Best for: Running LLMs locally with Python; Building OpenAI-compatible local inference servers; Prototyping with quantized models on consumer hardware
5. TextGen
The original local LLM interface. Text, vision, tool-calling, training, and more. 100% offline.
What sets it apart: Most feature-complete local LLM web UI with 4 inference backends, training, tool-calling, vision, and image gen — vs Ollama (CLI-focused) or LM Studio (closed source)
Best for: Running any LLM locally with a full-featured web UI; Privacy-conscious users wanting 100% offline AI; Developers needing a local OpenAI-compatible API server
6. Chat UI
The open source codebase powering HuggingChat
What sets it apart: Powers HuggingChat (huggingface.co/chat) — the most production-proven open-source chat UI with unique LLM Router for automatic model selection and native MCP tool support, unlike simpler UIs it handles multi-user, multi-model deployments
Best for: Self-hosting a ChatGPT-like interface for open-source models; Organizations wanting HuggingChat-quality UI for their own LLMs
7. OpenChat
LLMs custom-chatbots console ⚡
What sets it apart: vs Chatbase/CustomGPT: self-hosted open-source chatbot platform with unlimited memory, codebase ingestion for pair programming, and embeddable website widgets — own your data without SaaS vendor lock-in
Best for: Building knowledge-base chatbots from company documents; Website customer support widgets with custom data; Pair programming assistance using codebase context
8. Chatbot UI
AI chat for any model.
What sets it apart: vs ChatGPT web app: open-source, self-hosted with Supabase backend for full data ownership — the most popular open-source ChatGPT UI clone with 28k+ stars
Best for: Developers wanting a self-hosted ChatGPT-like UI with data persistence; Teams needing an open-source chat interface they can customize; Organizations wanting full control over their AI chat data
FAQ
- What are the best alternatives to FastChat?
- The closest open-source alternatives to FastChat are Text Generation Inference, vLLM and llama.cpp, followed by llama-cpp-python, TextGen and Chat UI. They are ranked by how closely they match what FastChat does.
- Which FastChat alternative is the most popular?
- llama.cpp has the most GitHub stars among FastChat alternatives, with 130,040 stars.
- Which FastChat alternative is the most actively maintained?
- By recent activity, vLLM (3,946 commits in the last 90 days) is the most actively developed alternative.