AutoGen is Microsoft's open-source framework for building multi-agent systems in code, and it has been one of the most influential projects in the space, the place a lot of engineers first learned to make several agents talk to each other and solve a task together (AutoGen on GitHub, retrieved 2026). Gravity is the opposite end of the same spectrum: no code, no orchestration, just describe an outcome and run a finished agent. Comparing them is really comparing a workshop full of power tools to a finished product on a shelf.

There is also a 2026 wrinkle worth stating up front: AutoGen is now in maintenance mode, with Microsoft pointing new work toward the Microsoft Agent Framework (Microsoft Learn, retrieved 2026). That does not make AutoGen useless, but it changes the math if you are choosing a foundation today. I will be specific about who each tool is for and where the line falls.

What AutoGen is in 2026

AutoGen is a programming framework for agentic AI. You write code that defines multiple agents, give each a role and tools, and let them converse to accomplish a goal, for example a planner agent that delegates to a coder agent that delegates to a critic agent. The stable maintenance line uses an asynchronous, actor-model architecture that is well suited to research and prototyping (AutoGen on GitHub, retrieved 2026). If you want the conceptual background, see multi-agent systems explained and AI agent orchestration explained.

What it gives developers

The appeal is control. You decide the conversation pattern, the tools, the termination conditions, and the guardrails. For a researcher exploring multi-agent behavior or an engineer who needs an orchestration pattern no product offers, that flexibility is the whole point. AutoGen is code-first and proud of it.

The Agent Framework transition

Microsoft has positioned the Microsoft Agent Framework as the enterprise-ready successor, combining AutoGen's simple agent abstractions with Semantic Kernel's enterprise features like state management, type safety, telemetry, and graph-based orchestration, and it shipped a 1.0 release for production (Microsoft DevBlogs, retrieved 2026). AutoGen continues in maintenance mode and the community fork AG2 lives on, but new long-term projects are being pointed at the successor. None of this is a knock on AutoGen's ideas; it is just the lifecycle you should know about before committing.

What Gravity does differently

Gravity is not a framework. There is nothing to import, no agents to define, no orchestration loop to debug. You describe the outcome you want in plain language, and Gravity matches you with an expert-built agent that runs it in about 60 seconds. The expert already designed whatever orchestration the task needs, tested it, and published it. You pay per use, where one dollar buys 1,000 credits, with no subscription. See how Gravity works.

Whether a given task uses one agent or several behind the scenes is the builder's problem, not yours. That is the inversion: AutoGen exposes the multi-agent machinery so you can shape it; Gravity hides it so you can ignore it.

The three-sided marketplace

Gravity has three sides. Users run agents and pay per run. Builders publish agents and earn 20% of every run as pure profit. Creators earn 10% on runs from people they refer. An engineer who loves AutoGen could, in principle, be a Gravity builder: design the multi-agent system once, publish it, and earn every time a non-technical user runs it. For the builder economics, see how to monetize AI agents.

Side-by-side comparison

Across the dimensions that decide a real purchase, the contrast is stark. This is a build-tool-versus-product comparison, and the table reflects that.

DimensionAutoGenGravity
CategoryOpen-source multi-agent frameworkMarketplace of task agents
InterfaceCode, mostly PythonPlain-language text prompt
Who builds the agentYou do, in codeVetted expert builders
Target userDevelopers and researchersNon-technical operators
Lifecycle status (2026)Maintenance mode; successor is Microsoft Agent FrameworkPre-launch, actively building
Setup timeAn engineering projectDescribe outcome, run in about 60 seconds
Who owns reliabilityYou doBuilder and platform
CostFree framework plus model, compute, and engineering costPay per use, $1 = 1,000 credits
Earning modelBuild for your own useBuilders earn 20%, creators 10%

If you read that table and felt drawn to the left column, you are a builder and AutoGen or its successor is your world. If the right column reads like relief, you want a marketplace.

Code orchestration vs no build

The defining difference is not features, it is whether you write and own code. AutoGen is for people who want to express an idea as a multi-agent system and have the skills to do it. The reward is total control over behavior; the cost is that you carry the design, the debugging, the model bills, and the 2am pages when an agent loop misbehaves in production.

Gravity removes all of that by removing the build. You are not choosing a worse framework; you are choosing not to use a framework at all. This is the same axis I lay out in build vs buy AI agent. For readers who specifically wanted multi-agent capability without Python, our roundups of best LangChain alternatives for non-developers and open-source AI agent frameworks map the rest of the landscape.

The maintenance-mode question

If you are starting a project today, AutoGen's maintenance status matters more than any feature checkbox. Building a multi-year system on a framework whose maintainer is steering new work elsewhere is a real risk, even with a healthy community fork. Microsoft's own migration guidance points AutoGen and Semantic Kernel users to the Agent Framework (Microsoft Learn, retrieved 2026).

This is exactly the kind of platform-longevity risk that a marketplace shifts off your shoulders. When you run an agent on Gravity, the question of which framework it was built on, and whether that framework is still maintained, is the builder's concern. You consume the outcome. That is a quieter benefit of the buy side that rarely shows up on a feature comparison but matters a lot over years.

Pricing reality

AutoGen the framework is free and open source. The real cost is everything around it: model API calls, compute, and the engineering time to build, test, and maintain a multi-agent system, which for a production system dwarfs any license fee. "Free framework" is not the same as "free outcome."

Gravity is in pre-launch waitlist in 2026 and prices the outcome directly: one dollar buys 1,000 credits, spent only on runs you trigger, with no engineering line item at all. For how to reason about total cost across approaches, see AI agent cost models explained.

When AutoGen is the right choice

Three signals point to AutoGen, or its successor. First, you are a developer or researcher and the control of a code framework is the point, not a burden. Second, your use case is novel enough that no finished product covers it and you genuinely need to design the orchestration. Third, you have the team to own the system long term, including the migration path as the ecosystem shifts to the Agent Framework.

If that is you, embrace the build, and treat the maintenance-mode note as a nudge to evaluate the successor rather than a reason to avoid the family.

When Gravity is the right choice

Three opposite signals point to Gravity. First, you want a task done, not a system built; Python is not on your menu. Second, you would rather inherit an expert's tested agent than own orchestration, reliability, and framework risk yourself. Third, you want to pay per run, not carry the standing cost of a system you operate.

The marketplace bet is that as experts publish more finished agents, the value of every team rebuilding the same orchestration from scratch falls. For why I made that bet, see about Gravity, and for a closer-category comparison, our Gravity vs CrewAI and Gravity vs LangChain breakdowns.

Using both together

The healthiest relationship is builder-to-marketplace. An engineer can use AutoGen, or the Agent Framework, to design a sophisticated multi-agent system, then publish it as a finished agent on Gravity so non-technical operators can run it and the builder earns per run. The framework is where the cleverness happens; the marketplace is where distribution, billing, and discovery are solved. One feeds the other.

Frequently asked questions

What is AutoGen?

AutoGen is Microsoft's open-source programming framework for building multi-agent AI systems in code, mostly Python. Developers define multiple agents that converse and collaborate to solve a task. As of 2026 AutoGen is in maintenance mode, with Microsoft pointing new projects to the Microsoft Agent Framework, its enterprise-ready successor.

What is the main difference between AutoGen and Gravity?

AutoGen is a developer framework: you write code to orchestrate multiple agents. Gravity is a marketplace: a non-developer describes an outcome and runs a finished agent an expert already built. AutoGen gives engineers the building blocks for multi-agent systems; Gravity gives operators the finished result with no code.

Is AutoGen still maintained in 2026?

AutoGen is in maintenance mode and is community managed, with Microsoft steering new work toward the Microsoft Agent Framework, which merges AutoGen's agent abstractions with Semantic Kernel's enterprise features. A community fork called AG2 also continues. Confirm the current status on the AutoGen GitHub before starting a long-lived project on it.

Is Gravity a no-code alternative to AutoGen?

In spirit, yes, but it is more accurate to call it a no-build alternative. AutoGen needs you to design and code an agent system. Gravity removes the build entirely: you do not assemble agents, you run one an expert already built and tested. If you wanted multi-agent power without writing Python, a marketplace is one path to it.

When should I choose AutoGen over Gravity?

Choose AutoGen when you are a developer who needs fine-grained control over how multiple agents reason, talk, and call tools, and you are comfortable owning and maintaining that code. Choose Gravity when you want a defined task done by a tested agent and have no interest in writing or running an orchestration framework.

How much does AutoGen cost?

AutoGen itself is open source and free, but you pay for the model API calls, compute, and engineering time to build and run your system, which is the larger real cost. Gravity is in pre-launch waitlist in 2026 and prices per use, where one dollar buys 1,000 credits, with the build and maintenance cost removed entirely.

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