Agent infrastructure · agent infrastructure component
OmniRoute: review, pricing, security and alternatives
OmniRoute is an open-source agent infrastructure component published by cheaper-inference, in the agent infrastructure family. A model gateway that unifies providers and manages request routing, quotas, and fallback for AI coding assistants. Its repository has 80,653 stars and its last commit is from October 23, 2026.
What OmniRoute does
OmniRoute belongs to the agent infrastructure family: technical building blocks for agents: memory, execution sandboxes, model gateways, observability, evaluation. On our grid it ranks #1 of the 28 projects of this family listed in the directory.
It is not an agent in itself: it is a component other agents use (memory, isolated execution, web access, model gateway or monitoring). You pick it based on the agent or framework it has to equip.
You use it from: API, web app, and desktop app. Usable models: Kimi (Moonshot), Claude (Anthropic), GPT (OpenAI), Gemini (Google), GLM (Zhipu), DeepSeek, and any OpenAI-compatible model. It can run on your own machine or server.
Who is OmniRoute for?
It is for teams running agents in production that need a reliable component: isolated execution, memory, model gateway or observability. Typical tasks people give it:
- isolate code generated by an agent
- track model call costs and errors
- give an agent long-term memory
It is a good candidate if you prefer doing everything in a browser, with no install and your data must stay on your machines.
Access and human control
Its documentation does not detail the access granted to the agent: check the settings before connecting it to your accounts.
We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.
OmniRoute pricing
The code is free, under the MIT licence.
Getting started with OmniRoute
- Install it: the project ships as a Node.js package (install with
npm, or run directly withnpx). The exact command is in the repository README. - Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
- Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.
Security: risk level
An infrastructure component sees prompts, keys and data pass through: self-host it or read the service's retention policy.
Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.
Project activity and releases
Created on February 13, 2026, the cheaper-inference/OmniRoute repository has 80,653 stars, 11,782 forks and 141 open issues, with 11,520 commits in total. It received changes this month.
Over the last 52 weeks: 14,009 commits, an average of 269.4 per week.
282 releases in total; 30 in the last twelve months. Latest release: v3.8.52, on October 19, 2026.
OmniRoute vs other agent infrastructure
GitHub stars of the best-rated open-source projects in the agent infrastructure family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.
OmniRoute and other agent infrastructure at a glance
The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.
| Agent | Model | Score | Stars or entry price | Self-hostable | Human approval |
|---|---|---|---|---|---|
| OmniRoute | open source | 90 | 80.7K ★ | yes | – |
| Mem0 | open source | 89 | 67.7K ★ | yes | – |
| Firecrawl | open source | 86 | 194.9K ★ | yes | – |
| Claude-Mem | open source | 86 | 102.8K ★ | yes | – |
| Cognee | open source | 85 | 32.7K ★ | yes | – |
| 9Router | open source | 85 | 31.3K ★ | yes | – |
| Hyperframes | open source | 84 | 71.3K ★ | yes | – |
| Crawl4AI | open source | 83 | 86.2K ★ | yes | – |
How we rated it
Score: 90/100, computed only from public, verifiable data, with no subjective testing or partnership:
- Adoption 35/40: 80,653 stars on a log scale (40 points from about 200,000).
- Activity 30/30: last commit less than a month ago, 30 releases in six months, 14,009 commits in a year.
- Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.
The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.
Verdict
OmniRoute is one of the most solid projects in its family: followed, active and well framed.
Strengths
- Widely followed: 80.7K stars
- Very active development
- Frequent releases (30 in a year)
- Can run on your side: data under control
- Free choice of model
Alternatives
- Mem067.7K ★
- Firecrawl194.9K ★
- Claude-Mem102.8K ★
- Cognee32.7K ★
- 9Router31.3K ★
- Hyperframes71.3K ★
Learn more
Frequently asked questions
Is OmniRoute free?
The software is free (MIT licence). You still pay for the model calls, unless you use a local model.
Is OmniRoute safe?
Our risk level: low. Give it minimum rights and approve irreversible actions.
Which models does OmniRoute use?
According to its documentation: Kimi (Moonshot), Claude (Anthropic), GPT (OpenAI), Gemini (Google), GLM (Zhipu), DeepSeek, and any OpenAI-compatible model.
Can OmniRoute be installed on your own server?
Yes, from the cheaper-inference/OmniRoute repository. Data then stays with you, but security and updates are your job.
What are the alternatives to OmniRoute?
In the same family: Mem0, Firecrawl, Claude-Mem, and Cognee.
OmniRoute or Mem0: what is the difference?
Both belong to the agent infrastructure family. OmniRoute has 80.7K stars against 67.7K for Mem0. The right choice mostly depends on the access you are willing to give it.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score