Ollama vs Ray
On the evidence we track, Ollama leads this comparison with a composite score of 80/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Ollama
LeaderA platform for running open-source language models through CLI, API, or desktop interfaces, with broad integration support for development tools. Provides both private local execution and cloud-hosted inference while maintaining strict data privacy and refusing to train on user inputs.
Ray
Ray is an open-source unified framework for scaling Python and machine learning applications across any infrastructure. It provides distributed compute primitives, specialized AI libraries for data processing, model training, tuning, and serving, with seamless scaling from development environments to large clusters.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Ollama
LeaderFree tier available. Paid plans from $20/mo (Pro) to $100/mo (Max) for individuals; $25/seat/mo for teams (min. 5 seats).
- FreeFree
- Unlimited public models
- 40,000+ community integrations
- CLI, API, and desktop apps
- Run models on your own hardware
- Access cloud models
- +1 more
- Pro$20/mo or $200/year
- Everything in Free
- Access larger, more powerful cloud models
- Run 3 cloud models concurrently
- Upload and share private models
- Extra usage balance available
- Max$100/mo (new signups paused)
- Everything in Pro
- Run 10 cloud models concurrently
- Extra usage balance available
- Team$25/seat/mo (minimum 5 seats = $125/mo)
- Access to powerful open models in US and Europe
- High performance (up to 2x faster than competing gateways)
- Zero data retention and logging
- Shared billing and administration
- Priority support
- +6 more
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
Ollama
Leader- Claude Code
- OpenClaw
- OpenCode
- Codex
- Copilot
- Droid
- Open WebUI
- Onyx
- LibreChat
- Lobe Chat
- NextChat
- Perplexica
- big-AGI
- Lollms WebUI
- ChatOllama
- Bionic GPT
- Chatbot UI
- Hollama
- Chatbox
- Ollama RAG Chatbot
- Dify.AI
- AnythingLLM
- Maid
- Witsy
- +40 more
Ray
- PyTorch
- TensorFlow
- AIBrix
- AReaL
- Cosmos Curate
- Daft
- Data-Juicer
- DeltaCAT
- Modin
- NeMo Curator
- NeMo-RL
- OpenRLHF
- RayDP
- ROLL
- SkyRL
- SLIME
- Syftr
- verl
- vLLM
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.