head to head · open source

Ollama vs Arize Phoenix

Ollama has 181,161 GitHub stars, 17,917 forks, 3,957 open issues and last shipped yesterday. Arize Phoenix has 11,518 stars, 1,135 forks, 970 open issues and last shipped yesterday. Ollama leads on adoption by 1,473% (181,161 vs 11,518 stars). Ollama is written in Go under MIT; Arize Phoenix is written in Python under a custom or non-standard licence. Ollama has attracted 10% as many forks as stars, Arize Phoenix 10%. Arize Phoenix 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.

Ollama ★ 181K Arize Phoenix ★ 12K category AI & Machine Learning

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Side by side

Ollama Arize Phoenix
GitHub stars ★ 181K ★ 12K
License MIT Custom / other
Written in Go Python
Last push 2026-09-17 2026-09-17
Forks ⑂ 18K ⑂ 1.1K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Ollama if

  • You weight community size — 181K stars and counting
  • You want the MIT license terms
  • Your stack matches Go
  • You value the larger contributor base for long-term maintenance

full Ollama profile →

pick Arize Phoenix if

  • You want the Arize Phoenix feature set and don't need the biggest community
  • You prefer the Custom / other license terms
  • Your stack matches Python
  • You evaluated both and Arize Phoenix fits your workflow better

full Arize Phoenix profile →

About Ollama

Ollama is a Go based, MIT licensed runtime that downloads and runs open source large language models such as DeepSeek, Qwen, Gemma, GLM, MiniMax and gpt oss locally on a user's own machine, and it is aimed at developers and teams that want model inference without routing prompts through a hosted API.

read the full Ollama overview →

About Arize Phoenix

Arize Phoenix is an open source AI observability platform for experimentation, evaluation, and troubleshooting. It lives in the machine learning infrastructure ecosystem and is written in Python. The project provides tracing, evaluation, datasets, experiments, prompt management, and a playground for LLM applications.

read the full Arize Phoenix overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K ponytail ★ 141K

Related comparisons

ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai ollama vs pageindex ollama vs langfuse llama-cpp vs vllm 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.

Ollama vs llama.cpp Ollama vs vllm Ollama vs GPT4All Ollama vs llama_index Ollama vs LocalAI Ollama vs PageIndex Ollama vs Langfuse Ollama vs cognee Ollama vs taipy Ollama vs dagster Ollama vs zvec Ollama vs langchain4j

Frequently asked questions

Is Ollama or Arize Phoenix more popular?

Ollama has 181,161 GitHub stars and Arize Phoenix has 11,518. Ollama has the larger community by that measure.

Are Ollama and Arize Phoenix free?

Both are open source. Ollama is licensed under MIT, and Arize Phoenix has no licence declared in this registry. Both are free to self-host.

What is the difference between Ollama and Arize Phoenix?

Ollama is written in Go and Arize Phoenix 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, Ollama or Arize Phoenix?

Choose Ollama if you want the larger community (181,161 stars) or its MIT licence terms. Choose Arize Phoenix if its feature set, stack or Custom / other licence fits better. Both are self-hostable.