Swarm: review, pricing, security and alternatives

What Swarm does

Swarm belongs to the multi-agent family: systems that split a task between several specialised agents passing work to one another. On our grid it ranks #40 of the 43 projects of this family listed in the directory.

Unlike a ready-made agent, a framework provides the parts to build one: tool calling, step sequencing, memory, coordination of several agents. It is aimed at teams that want a custom agent.

You use it from: developer SDK. Usable models: GPT (OpenAI). It can run on your own machine or server.

Who is Swarm for?

It interests technical teams that want to split a complex task between several specialised agents that check each other. Typical tasks people give it:

• pair a writer agent with a reviewer agent
• split a project into subtasks given to roles
• simulate a team (analysis, plan, execution)

It is a good candidate if your data must stay on your machines.

Access and human control

A framework has no access of its own: the tools you plug in define what the agent can do. Start with read-only tools.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Swarm pricing

The code is free, under the MIT licence.

Getting started with Swarm

1. Install it: the project ships as a Python package (install with pip or uv). The exact command is in the repository README.
2. Create an API key with the model provider and put it in an environment variable, never in a shared or versioned file.
3. Start with the minimal example from the docs, then add one tool at a time and check what the agent does with it.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

More agents mean higher bills and chained errors: set a budget and a maximum number of steps.

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 22, 2024, the openai/swarm repository has 22,074 stars, 2,345 forks and 29 open issues, with 29 commits in total. Last change 6 months ago.

Over the last 52 weeks: 1 commits, an average of 0 per week.

The project publishes no numbered releases on GitHub: you install it from the main branch or a package manager.

Swarm vs other multi-agent

GitHub stars of the best-rated open-source projects in the multi-agent family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

Swarm and other multi-agent 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.

How we rated it

Score: 48/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 28/40: 22,074 stars on a log scale (40 points from about 200,000).
• Activity 5/30: last commit 6 months ago, 0 releases in six months, 1 commits in a year.
• Framework 15/30: 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.