CrewAI vs LlamaIndex: Which Agent Fwk (2026)

CrewAI and LlamaIndex solve different problems: CrewAI orchestrates role-based multi-agent teams, while LlamaIndex Workflows is a RAG-centric, event-driven engine for document pipelines. Both are MIT-licensed Python and both point at Chinese LLM APIs unchanged. The right pick is decided by your workload, not by star count, and we pulled both repos live on 2026-07-10 to keep the comparison honest.

If you are staffing a job that looks like a team of specialists handing work to each other, CrewAI is built for that shape. If the job is "answer questions over my documents" or "run a multi-step retrieval pipeline," LlamaIndex Workflows was designed around that event flow first. This piece compares the two head to head, with a dated GitHub snapshot for each, so you can decide by use case instead of hype.

CrewAI vs LlamaIndex GitHub snapshot (verified 2026-07)

We checked both repositories on 2026-07-10 via the GitHub API. Star counts and release dates move, so treat every number here as a dated snapshot rather than a permanent fact.

According to CrewAI on GitHub, the project carried 55,260 stars and shipped release 1.15.2 on 2026-07-08 when we read it. The recency matters more than the raw total: a release two days before our snapshot signals an actively maintained core, which is the thing a buyer evaluating a framework for production actually needs to know.

According to LlamaIndex on GitHub, the repository held 50,751 stars under an MIT license, with v0.14.23 dated 2026-06-24. The two projects sit within roughly 4,500 stars of each other, close enough that popularity is not a tiebreaker. What separates them is architecture, which is where the decision should be made.

First-hand evidence: what the live repos showed

Documentation and blog roundups go stale fast, so we pulled the numbers ourselves rather than trusting a secondhand table. As of 2026-07-10, per the GitHub API, CrewAI reported 55,260 stars, an MIT license, and latest release 1.15.2 dated 2026-07-08, with 632 open issues. LlamaIndex reported 50,751 stars, MIT license, and latest release v0.14.23 dated 2026-06-24, with 508 open issues and a last push on 2026-07-08.

The open-issue counts are worth a second look. CrewAI's 632 against LlamaIndex's 508 is not a defect ratio; both are large, active projects where open issues track adoption as much as bugs. The signal we care about is that both repos pushed commits within days of our snapshot, which is the maintenance heartbeat you want before betting a production pipeline on either.

How the two frameworks differ in design

CrewAI is a multi-agent orchestration framework that models work as a crew of role-assigned agents (a researcher, a writer, a reviewer) collaborating toward a goal. Its recent 1.14.x line added pluggable backends and a Chat API, which widened where the agents can run. The mental model is a team: you define roles, tasks, and how they hand off.

LlamaIndex Workflows is an event-driven orchestration layer that grew out of a RAG toolkit, so retrieval, indexing, and document reasoning are first-class rather than bolted on. The Workflows 1.0 release landed in June 2026 and reframes multi-agent flows as steps reacting to typed events. The mental model is a pipeline: events fire, steps consume them, and the graph advances.

According to the CrewAI repository, the framework is model-agnostic, which is the property that lets it target Chinese LLM APIs. Point either framework's client at an OpenAI-compatible endpoint from DeepSeek, Qwen, or Zhipu GLM, and role agents or workflow steps run on those models without a rewrite. That portability is the reason both frameworks are on-topic for a China-LLM directory in the first place.

Which one to choose

Pick by the shape of your problem, not by the leaderboard:

• Choose CrewAI when the work decomposes into distinct roles that pass artifacts between them: a research agent gathering sources, a writer drafting, a critic reviewing. Role-based delegation is the native abstraction, and you spend less code fighting the framework.
• Choose LlamaIndex Workflows when the core job is retrieval over your own documents, or any multi-step pipeline where each step reacts to the output of the last. If "RAG" is in your requirements doc, start here.
• Either works for general tool-calling agents, and both run on Chinese LLM APIs, so if cost is the deciding factor, the framework choice is neutral and you optimize on the model instead. Our live model-cost runs, alongside the best Chinese LLM API breakdown, are where that call gets made.

A practical note for teams already invested in an ecosystem: LlamaIndex carries a large library of data connectors and index types built over years as a RAG framework, so a document-heavy team inherits more off-the-shelf plumbing there. CrewAI's advantage is conceptual simplicity for the team-of-agents pattern, where LlamaIndex's event graph can feel heavier than the job requires.

FAQ

Is CrewAI or LlamaIndex more popular on GitHub? CrewAI is marginally ahead. As of 2026-07-10 we read 55,260 stars for CrewAI against 50,751 for LlamaIndex, a gap of about 4,500 stars, which is close enough that popularity should not decide your choice. Both are MIT-licensed Python projects with releases shipped within the prior three weeks.

Can CrewAI and LlamaIndex use Chinese LLM APIs like DeepSeek or Qwen? Yes. Both are model-agnostic and accept OpenAI-compatible endpoints, so pointing either at DeepSeek, Qwen, or GLM is a configuration change, not a rewrite. The role agents (CrewAI) or workflow steps (LlamaIndex) then run on the Chinese model you selected.

What is the core difference between CrewAI and LlamaIndex Workflows? CrewAI models work as a crew of role-based agents that delegate to each other, while LlamaIndex Workflows is an event-driven engine that grew from a RAG toolkit and treats retrieval and document pipelines as first-class. Teams pick CrewAI for agent roles and LlamaIndex for document-centric pipelines.

Are both frameworks free to use commercially? Yes. We verified on 2026-07-10 that both CrewAI (release 1.15.2) and LlamaIndex (v0.14.23) are MIT-licensed, which permits commercial use, modification, and redistribution with attribution. The MIT license is one of the most permissive in open source.

Which framework is better for a RAG application? LlamaIndex Workflows. It began life as a RAG framework, so its connectors, index types, and retrieval steps are native rather than added later. CrewAI can call retrieval tools, but if document question-answering is the central job, LlamaIndex gives you more built-in plumbing.

This comparison is part of our open-source AI agents 2026 hub, which ranks the trending frameworks side by side. For choosing the model underneath, see the best Chinese LLM API guide.

Author: Kevin Fan, Customer Success Manager at China LLM Directory, specializing in the Chinese LLM ecosystem and open-source agent tooling. Last verified: 2026-07-10.