head to head · open source

LocalAI vs dagster

LocalAI has 49,147 GitHub stars, 4,457 forks, 201 open issues and last shipped today. dagster has 16,168 stars, 2,294 forks, 2,589 open issues and last shipped today. LocalAI leads on adoption by 204% (49,147 vs 16,168 stars). LocalAI is written in Go under MIT; dagster is written in Python under Apache-2.0. LocalAI has attracted 9% as many forks as stars, dagster 14%. LocalAI was the more recently maintained of the two, and both are self-hostable with no licence fee.

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 dagster ★ 16K category AI & Machine Learning

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Side by side

LocalAI dagster
GitHub stars ★ 49K ★ 16K
License MIT Apache-2.0
Written in Go Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 4.5K ⑂ 2.3K
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 dagster if

  • You want the dagster 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 dagster fits your workflow better

full dagster 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 dagster

Dagster is a cloud native data pipeline orchestrator written in Python and released under the Apache 2.0 licence, built for data engineers, data scientists, and machine learning teams who declare the tables, data sets, models, and reports their pipelines should produce and need those assets tested, observable, and kept up to date from local development through production.

read the full dagster overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

ollama vs localai ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index llama-cpp vs vllm ollama vs pageindex ollama vs langfuse openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow

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 PageIndex LocalAI vs Langfuse LocalAI vs cognee LocalAI vs taipy LocalAI vs zvec LocalAI vs langchain4j LocalAI vs txtai

Frequently asked questions

Is LocalAI or dagster more popular?

LocalAI has 49,147 GitHub stars and dagster has 16,168. LocalAI has the larger community by that measure.

Are LocalAI and dagster free?

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

What is the difference between LocalAI and dagster?

LocalAI is written in Go and dagster 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 dagster?

Choose LocalAI if you want the larger community (49,147 stars) or its MIT licence terms. Choose dagster if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.