head to head · open source
Ollama vs mlop
Ollama has 185,702 GitHub stars, 18,873 forks, 3,957 open issues and last shipped yesterday. mlop has 394 stars, 12 forks, 3 open issues and last shipped 8 months ago. Ollama leads on adoption by 47,032% (185,702 vs 394 stars). Ollama is written in Go under MIT; mlop is written in Python under Apache-2.0. Ollama has attracted 10% as many forks as stars, mlop 3%. Ollama 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.
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Side by side
| Ollama | mlop | |
|---|---|---|
| GitHub stars | ★ 186K | ★ 394 |
| License | MIT | Apache-2.0 |
| Written in | Go | Python |
| Last push | 2026-11-02 | 2026-03-05 |
| Forks | ⑂ 19K | ⑂ 12 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Ollama if
- You weight community size — 186K stars and counting
- You want the MIT license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick mlop if
- You want the mlop 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 mlop fits your workflow better
About Ollama
Ollama Start building with open models. Download macOS or download manually Windows or download manually Linux Manual install instructions Docker The official Ollama Docker image ollama/ollama is available on Docker Hub. Libraries ollama python ollama js Community Discord 𝕏 (Twitter) Reddit Get started You'll be prompted to run a model or connect Ollama to your existing agents or applications such as Claude Code , OpenClaw , OpenCode , Codex , Copilot , and more. Coding To launch a specific integration: Supported integrations include Claude Code, Codex, Copilot CLI, DeepSeek Harness, Droid, and OpenCode. AI…
read the full Ollama overview →
About mlop
mlop is a Machine Learning Operations (MLOps) framework. It provides self hostable superior experimental tracking capabilities and lifecycle management for training ML models. To get started, try out our introductory notebook or get an account with us today! 🎥 Demo mlop adopts a KISS philosophy that allows it to outperform all other tools in this category. Supporting high and stable data throughput should be THE top priority for efficient MLOps. mlop logger (bottom left) v. a conventional logger (bottom right) 🚀 Getting Started Try mlop on our platform in a notebook & start integrating in just 5 lines of…
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Frequently asked questions
Is Ollama or mlop more popular?
Ollama has 185,702 GitHub stars and mlop has 394. Ollama has the larger community by that measure.
Are Ollama and mlop free?
Both are open source. Ollama is licensed under MIT and mlop under Apache-2.0. Neither carries a licence fee.
What is the difference between Ollama and mlop?
Ollama is written in Go and mlop 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 mlop?
Choose Ollama if you want the larger community (185,702 stars) or its MIT licence terms. Choose mlop if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.