Best framework for building AI agents

Combined ranking

1. 1
   LangGraph—20 pts

   GPT #1Claude #1Gemini #1Grok #1

   Best production-grade agent orchestration: durable state, graph control, human-in-the-loop, streaming, memory, LangSmith observability, broad ecosystem adoption

   To stay #1 Simplify the developer experience and reduce LangChain ecosystem complexity

2. 2
   CrewAI—11 pts

   GPT #5Claude #4Gemini #2Grok #2

   Offers an intuitive, role-based orchestration layer that enables rapid development of collaborative agent teams with minimal boilerplate.

   To rank higher Improve predictability of agent execution paths and native support for highly complex cyclic state machines.

3. 3
   OpenAI Agents SDKincumbent—9 pts

   GPT #3Claude #2Gemini —Grok #4

   Cleanest developer experience for getting a multi-agent system running — handoffs, guardrails, sessions, and built-in tracing in a minimal Python/TS API; tight integration with the Responses API and OpenAI's tool ecosystem makes it the fastest path from idea to working agent

   To rank higher True model-agnosticism — it works best inside OpenAI's stack, and deeper first-class support for non-OpenAI models and self-hosted deployment would broaden it beyond OpenAI-committed teams

4. 4
   AutoGenincumbent▲15 pts

   GPT #4Claude —Gemini #3Grok —

   Features a powerful, conversation-centric architecture with robust support for code execution and flexible multi-agent interaction patterns.

   To rank higher Streamline production deployment capabilities and standardize state management across its diverse language SDKs.

5. 5
   Google ADK▲25 pts

   GPT #2Claude #5Gemini —Grok —

   Strongest cloud-native path from local agent code to deployed enterprise agents, with Gemini, Vertex AI, evaluation, observability, identity, and A2A alignment

   To rank higher Prove equal strength outside Google Cloud and Gemini-centric stacks

6. 6
   CClaude Agent SDK▼23 pts

   GPT —Claude #3Gemini —Grok —

   Battle-tested harness extracted from Claude Code — the strongest out-of-the-box agent loop (tool use, file/bash access, subagents, MCP support, context compaction) so you inherit production-grade agentic behavior instead of building it; excels at long-running autonomous coding and computer-use tasks

   To rank higher First-class multi-provider support — it's designed around Claude models, and teams wanting model portability across vendors have to look elsewhere

7. 7
   Microsoft Agent Frameworknew3 pts

   GPT —Claude —Gemini —Grok #3

   Unified enterprise solution merging AutoGen and Semantic Kernel strengths with .NET integration, async multi-agent conversations, security, and governance for large orgs

   To rank higher Broaden model-agnostic flexibility beyond Microsoft ecosystem

8. 8
   LlamaIndex▼22 pts

   GPT —Claude —Gemini #4Grok —

   Excels at data-driven workflows, seamlessly connecting advanced RAG pipelines with event-driven agent orchestration.

   To rank higher Enhance native coordination patterns for non-data-centric multi-agent chat structures.

9. 9
   LLlamaIndex Workflowsnew1 pts

   GPT —Claude —Gemini —Grok #5

   Superior for RAG-grounded and knowledge-intensive agents with robust retrieval, indexing, and agentic workflows on private data

   To rank higher Enhance general multi-agent orchestration beyond retrieval-focused strengths

10. 10
    Semantic Kernel▼21 pts

    GPT —Claude —Gemini #5Grok —

    Delivers enterprise-grade, strongly-typed integration for multi-language environments with native support for safety guidelines.

    To rank higher Align documentation and feature parity between C# and Python implementations to lower adoption barriers.

Rank history

By model

Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled continuously