CrewAI vs AutoGen in 2026: Features, Pricing and Use Cases
CrewAI is the stronger choice for small businesses in 2026: its open-source Python framework is free with no execution limits, and its hosted AMP platform starts free with 50 workflow executions per month, while AutoGen entered maintenance mode in October 2025 and no longer receives new features. AutoGen remains a completely free, Apache 2.0-licensed multi-agent conversation framework with roughly 42,000 GitHub stars, and Microsoft points new users to its successor, Microsoft Agent Framework. If you want to extend either framework with vetted, security-scanned agent skills, SkillzBench's free skills directory and free MCP connector (currently in pre-launch, waitlist open) are worth watching.
TL;DR
- CrewAI's open-source framework is free and unlimited when self-hosted; you pay only for LLM API calls and hosting.
- CrewAI's hosted AMP platform starts free with 50 workflow executions per month; third-party sources report a Pro tier at $25/month (100 executions) and AMP Cloud around $99/month.
- AutoGen is completely free under the Apache 2.0 license, but it entered maintenance mode in October 2025 and receives no new features.
- Microsoft's AutoGen README now directs new users to Microsoft Agent Framework, which reached 1.0 GA in April 2026.
- CrewAI is on v1.15.x with 235+ releases and removed its LangChain dependency as of v1.14, making it fully standalone.
- CrewAI's role-based architecture (agents with roles, goals, backstories) is often cited as the fastest route from idea to working multi-agent prototype.
- Both frameworks require coding: CrewAI needs solid Python skills, and AutoGen is a Python/.NET developer framework, not a no-code tool.
Head to head
| Dimension | CrewAI | AutoGen |
|---|---|---|
| Pricing | Free open-source framework; AMP Basic free with 50 executions/mo; Pro reported at $25/mo; AMP Cloud reported around $99/mo; Enterprise custom | Completely free, Apache 2.0 open source |
| Ease of use | Intuitive role-based team metaphor; fastest prototyping, but solid Python skills realistically required 🏆 | Conversation-based model; medium learning curve, code-first |
| Features | Crews + Flows, unified memory, 60+ built-in tools, visual Studio, tracing, guardrails, MCP export 🏆 | Multi-agent conversation abstractions, enhanced LLM inference optimization; feature set frozen |
| Support | Community support on free tiers; dedicated support, Slack/Teams contact and on-site training on Enterprise 🏆 | Community managed only |
| Integrations | Any LLM provider (OpenAI, Anthropic, Groq, Ollama), GitHub integration, enterprise connectors on paid tiers 🏆 | Python and .NET; broad LLM compatibility, but new capabilities land in Microsoft Agent Framework |
| Setup | pip-installable framework; two-agent crew in under 30 lines of code; self-host or use AMP cloud 🏆 | Install and wire agents yourself; no hosted platform tier |
| Future-proofing | Actively developed: v1.15.x, 235+ releases, LangChain dependency removed 🏆 | Maintenance mode since October 2025; successor is Microsoft Agent Framework (1.0 GA April 2026) |
The contenders
CrewAI is an open-source Python framework for orchestrating teams of AI agents in role-based, collaborative setups. You define agents with a role, a goal and a backstory, assign them tools, and group them into Crews that run tasks sequentially, hierarchically or (experimentally) by consensus. A second mode, Flows, adds event-driven, deterministic pipelines with conditions, loops, error handling and state for reproducible, auditable execution. As of v1.14 the framework is fully standalone, having removed its LangChain dependency, and it works with any LLM provider including OpenAI, Anthropic, Groq and local models via Ollama. Beyond the free framework, the paid AMP (Agent Management Platform) adds a visual Studio editor, tracing, guardrails, deployment infrastructure and enterprise governance such as SSO, RBAC and PII redaction. Reviewers consistently praise CrewAI's prototyping speed and intuitive team metaphor, while flagging steep Python requirements, coarse-grained error handling in production, and memory operations that get expensive at scale. It is best suited to technical teams building multi-step research, content and automation pipelines.
pricing 0/month
- + Genuinely free and unlimited open-source framework; you only pay for LLM API calls and hosting
- + Fastest time-to-prototype in the multi-agent space, with a two-agent crew achievable in under 30 lines of code
- + Fully standalone since v1.14 with no LangChain dependency, and no lock-in to any LLM provider
- + Strong community across GitHub, PyPI and Discord, with 235+ releases and active iteration (v1.15.x)
- + Broad feature surface on the paid platform: visual Studio, tracing, guardrails, human-in-the-loop, MCP export
- + Pre-built templates for common use cases like content production and research workflows
- − Requires solid Python skills despite no-code marketing; non-technical teams will struggle
- − Debugging multi-agent workflows is difficult; agent handoffs can pass incomplete context or ignore constraints
- − Error handling is coarse-grained for serious production use, and the gap between demo and reliable production is wider than in graph-based alternatives
- − Memory operations involve LLM calls, which get expensive with large agent teams
- − Model usage costs can spiral: a single complex research workflow may cost $10-50 in API credits
AutoGen is Microsoft's open-source multi-agent conversation framework, which abstracts LLM workflows as conversations between agents. It supports building diverse applications across domains, offers enhanced LLM inference APIs to improve performance and reduce cost, and runs in Python and .NET under the Apache 2.0 license. With roughly 42,000 GitHub stars, it has one of the largest communities in the agent-framework space and has been popular for multi-party conversation patterns and research-heavy projects. The critical 2026 context is its status: the AutoGen GitHub README states the project is now in maintenance mode, will not receive new features or enhancements, and is community managed going forward. Microsoft directs new users to Microsoft Agent Framework (MAF), the direct successor created by the same teams, which merges AutoGen's multi-agent abstractions with Semantic Kernel's enterprise features and reached 1.0 GA for .NET and Python in April 2026. Teams already on AutoGen can follow the published migration guide, but new platform capabilities such as typed-graph workflows and session-state management land in MAF, not AutoGen.
pricing 0
- + Completely free and open source under Apache 2.0
- + Large community with roughly 42,000 GitHub stars, more than CrewAI and LangGraph combined per one comparison
- + Proven multi-agent conversation abstractions, strong for multi-party dialogue and research use cases
- + Available in both Python and .NET, which CrewAI does not offer
- + Backed by a documented migration guide to Microsoft Agent Framework for teams wanting a supported path forward
- − In maintenance mode since October 2025: no new features or enhancements will be added
- − Now community managed, so issue resolution speed depends on volunteers rather than Microsoft staffing
- − Microsoft does not recommend it for new projects; the README points new users to Microsoft Agent Framework
- − New platform capabilities like typed-graph workflows and session-state management land in MAF, not AutoGen
- − Code-first framework with no hosted platform tier, so observability and deployment infrastructure are DIY
Verdict
Winner: CrewAI
For small businesses choosing a multi-agent framework in 2026, CrewAI is the safer bet: it is actively developed (v1.15.x, 235+ releases), free to self-host, and offers a managed cloud tier starting at free. AutoGen is capable but in maintenance mode, community-managed, and Microsoft directs new projects to Microsoft Agent Framework instead.
| Option | Overall | Breakdown |
|---|---|---|
| CrewAI | 8 | : 9: 6: 8: 7: 8: 8 |
| AutoGen | 5 | : 9: 6: 6: 4: 6: 2 |
Pricing compared
Features and architecture compared
The maintenance-mode question for 2026
Which should you pick?
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FAQ
Is CrewAI free to use?
Yes. The open-source framework is free with no artificial limits when you self-host; you pay only for your own LLM API calls and hosting. CrewAI's hosted AMP platform also has a free Basic tier with 50 workflow executions per month, a visual editor and GitHub integration. Third-party reviews report a Pro tier at $25/month for 100 executions and AMP Cloud at roughly $99/month, while Enterprise pricing is custom and adds SSO, RBAC, VPC deployment and dedicated support.
Is AutoGen still worth using in 2026?
It depends on your situation. AutoGen is completely free under Apache 2.0 and still works for existing conversation-based multi-agent workflows, with a large community of roughly 42,000 GitHub stars. However, it entered maintenance mode in October 2025, receives no new features, and is now community managed, meaning issue resolution depends on volunteers. Microsoft's own README directs new users to Microsoft Agent Framework, its successor, which reached 1.0 GA in April 2026. For new projects, most guidance points elsewhere.
Do I need to know Python to use CrewAI or AutoGen?
Yes, for both. CrewAI reviewers note that despite no-code marketing claims, building useful workflows realistically requires solid Python skills, and debugging multi-agent handoffs is genuinely difficult. AutoGen is likewise a code-first developer framework available in Python and .NET. Non-technical small-business owners looking for simple automation should consider no-code automation tools instead, or pair a developer resource with either framework.
What is Microsoft Agent Framework and how does it relate to AutoGen?
Microsoft Agent Framework (MAF) is the direct successor to AutoGen, created by the same teams. It merges AutoGen's multi-agent abstractions with Semantic Kernel's enterprise features, including session-based state management, type safety, filters and telemetry, and adds typed graph-based workflows with sequential, concurrent, handoff and group-collaboration patterns. It reached version 1.0 for both .NET and Python in April 2026 with stable APIs and a long-term support commitment. Microsoft's AutoGen README points new users to MAF and existing users to a migration guide.
How can I make agents from either framework use pre-built skills safely?
Agent skills (SKILL.md instruction packages) are widely shared, but quality and safety vary; published research found roughly 26% of skills carry at least one vulnerability. SkillzBench is building a free directory that crawls and dedupes skills from GitHub, pins every version to a commit SHA, runs security scans and license checks, and benchmarks each skill in a sandbox to publish its Lift in percentage points. Its free MCP connector lets you attach vetted skills to agents you build with frameworks like CrewAI. The platform is in pre-launch with a live waitlist.