9Router vs Ollama
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A local router that lets AI coding tools use multiple model providers, with fallback when limits hit.
Open source · MIT
Runs open AI models like Gemma, Qwen and DeepSeek on your own machine or in the cloud.
The short answer
Choose 9Router if you need…
- Developers who use AI coding tools and want to reduce spending
- People with several AI subscriptions who want to use up their quota
- Users who want one local endpoint for multiple AI providers
- Tinkerers willing to configure providers and model names by hand
Choose Ollama if you need…
- Developers who want a local model API for their own apps
- People who want to chat with open models without sending prompts to a hosted service
- Users who want to connect a coding assistant to a local or self-chosen model
- Students experimenting with different open models from a terminal
Side-by-side
| 9Router | Ollama | |
|---|---|---|
| Type | Dev tool | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 31.8k | 186k |
| Setup difficulty | Intermediate | Beginner |
| How you get it | Install with a package manager | Install with a package manager |
| Platforms | — | macOS, Windows, Linux, CLI, API |
| Works with | — | VS Code |
| Main language | JavaScript | Go |
| Last code update | 9 days ago | 4 days ago |
What each one is
9Router
9Router runs on your computer as a local server at localhost:20128. You point tools such as Claude Code, Codex, Cursor or Cline at it instead of a provider, and it forwards requests to one of 40+ AI providers. It can switch to a cheaper or free model when a primary subscription runs out, and its README says it compresses tool output to save tokens.
Ollama
Ollama is a tool for downloading and running open-weight AI language models locally, with a simple command line and a REST API. The README says it also offers cloud access and can connect to coding tools and assistants such as Claude Code, Codex and OpenClaw. People use it to try models privately or to build apps that call a model through a local API.
Best for
9Router
- Developers who use AI coding tools and want to reduce spending
- People with several AI subscriptions who want to use up their quota
- Users who want one local endpoint for multiple AI providers
- Tinkerers willing to configure providers and model names by hand
Ollama
- Developers who want a local model API for their own apps
- People who want to chat with open models without sending prompts to a hosted service
- Users who want to connect a coding assistant to a local or self-chosen model
- Students experimenting with different open models from a terminal
Strengths
9Router
- Single local endpoint works with many AI coding tools
- Automatic fallback between tiers of providers
- MIT licensed and open source with a large public following
Ollama
- Simple install and run commands across macOS, Windows, Linux and Docker
- Official Python and JavaScript libraries plus a documented REST API
- Large community with many integrations listed in the README
Not ideal for
9Router
- Users who need guaranteed uptime or enterprise support, since the README describes no such commitments
- People who do not want to manage API keys or provider accounts
- Anyone expecting every listed model to be truly unlimited, since free tiers and credits have limits the README itself mentions
Ollama
- People who need the most capable closed frontier models, since this focuses on open models
- Users with limited disk space or memory, because model files can be large and need capable hardware (the README does not give specific requirements)
- Non-technical users who want a polished desktop app with no terminal use, although the README mentions a download option for macOS and Windows
Trade-offs
9Router
- Free tiers and credits are limited and can change, so 'unlimited' is marketing wording
- Source-based setup and production build require extra steps and system tuning
- Relies on third-party providers whose terms and availability are outside the project's control
Ollama
- The README is truncated and does not state hardware requirements or model sizes
- Some features, such as cloud access and specific integrations, depend on Ollama's own services and documentation that is only partly described here
- Model quality and licensing depend on each individual model, not on Ollama itself
Getting started
9Router
Install globally with npm
npm install -g 9routerStart the router and dashboard
9routerOllama
macOS and Linux install
curl -fsSL https://ollama.com/install.sh | shWindows install (PowerShell)
irm https://ollama.com/install.ps1 | iexFrequently asked questions
What is the difference between 9Router and Ollama?
9Router: A local router that lets AI coding tools use multiple model providers, with fallback when limits hit. Ollama: Runs open AI models like Gemma, Qwen and DeepSeek on your own machine or in the cloud. 9Router suits developers who use ai coding tools and want to reduce spending, while Ollama suits developers who want a local model api for their own apps.
Are 9Router and Ollama free?
9Router: Free and open source. Ollama: Free and open source.
Which is easier to set up, 9Router or Ollama?
Ollama is easier to get started with (rated beginner); 9Router is rated intermediate and usually needs more setup.
Is 9Router or Ollama more popular?
Ollama has more GitHub stars (186k) than 9Router (31.8k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to 9Router and Ollama?
Other options people compare them with include wshobson/agents, planning-with-files, ECC, Claude Code Game Studios, codebase-memory-mcp.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.