head to head · open source

LocalAI vs FastDeploy

LocalAI has 49,179 GitHub stars, 4,458 forks, 201 open issues and last shipped today. FastDeploy has 3,716 stars, 756 forks, 649 open issues and last shipped 25 days ago. LocalAI leads on adoption by 1,223% (49,179 vs 3,716 stars). LocalAI is written in Go under MIT; FastDeploy is written in Python under Apache-2.0. LocalAI has attracted 9% as many forks as stars, FastDeploy 20%. LocalAI was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

LocalAI ★ 49K FastDeploy ★ 3.7K category AI & Machine Learning

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Side by side

LocalAI FastDeploy
GitHub stars ★ 49K ★ 3.7K
License MIT Apache-2.0
Written in Go Python
Last push 2026-09-20 2026-08-26
Forks ⑂ 4.5K ⑂ 756
Self-hosting Yes Yes
Data ownership Your server Your server

pick LocalAI if

  • You weight community size — 49K stars and counting
  • You want the MIT license terms
  • Your stack matches Go
  • You value the larger contributor base for long-term maintenance

full LocalAI profile →

pick FastDeploy if

  • You want the FastDeploy feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and FastDeploy fits your workflow better

full FastDeploy profile →

About LocalAI

LocalAI is an open source AI runtime that enables running large language models (LLMs), vision, audio, image, and video models locally or on premises. It operates as a modular engine where each model type is backed by a dedicated, lightweight backend—such as llama.cpp, whisper.cpp, or stable diffusion—pulled only when needed. This composable architecture avoids bundling unnecessary dependencies, keeping the core minimal while supporting diverse modalities and hardware configurations.

read the full LocalAI overview →

About FastDeploy

FastDeploy is a Python inference and deployment toolkit for large language models and vision language models in the PaddlePaddle ecosystem. It serves models such as ERNIE, ERNIE 4.5, ERNIE 4.5 VL, DeepSeek V3, Qwen3 MoE, Qwen3 VL, and PaddleOCR VL 0.9B on accelerators.

read the full FastDeploy overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

Related comparisons

ollama vs localai openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index open-webui vs gpt4all openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

LocalAI vs Ollama LocalAI vs llama.cpp LocalAI vs vllm LocalAI vs GPT4All LocalAI vs llama_index LocalAI vs faiss LocalAI vs PageIndex LocalAI vs Langfuse LocalAI vs cognee LocalAI vs taipy LocalAI vs dagster LocalAI vs zvec

Frequently asked questions

Is LocalAI or FastDeploy more popular?

LocalAI has 49,179 GitHub stars and FastDeploy has 3,716. LocalAI has the larger community by that measure.

Are LocalAI and FastDeploy free?

Both are open source. LocalAI is licensed under MIT and FastDeploy under Apache-2.0. Neither carries a licence fee.

What is the difference between LocalAI and FastDeploy?

LocalAI is written in Go and FastDeploy in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, LocalAI or FastDeploy?

Choose LocalAI if you want the larger community (49,179 stars) or its MIT licence terms. Choose FastDeploy if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.