Alternatives to LlamaIndex
Data framework for LLM apps and agents
LlamaIndex ranks #2 of 10 in AI agent frameworks, with an Alt Score of 96. It is licensed under MIT License and open source with paid hosting from $50/month (LlamaParse Starter). 13 of 13 checklist rows are verified against a public source.
LlamaIndex is a data framework for building LLM applications and agent workflows over your own data (RAG + agents).
Python (and, historically, JS/TS) developers building LLM applications and agents that need to reason over private or domain-specific data, from RAG chatbots and document agents to multi-agent workflows.
An open-source (MIT-licensed) data framework with data connectors, indexing, retrieval, and an event-driven Workflows/AgentWorkflow system for building single- and multi-agent applications with tool use, memory, streaming, human-in-the-loop, and observability integrations; LlamaCloud/LlamaParse adds a paid, hosted platform for document parsing, extraction, and managed RAG indexing.
Developers ingest and index data using LlamaIndex's connectors and index abstractions, then build agents or query/chat engines on top of that data using a model-agnostic LLM interface; more complex multi-step or multi-agent behavior is composed as an event-driven Workflow, which can be run locally or paired with LlamaCloud's hosted services for parsing and indexing at scale.
Why people leave LlamaIndex
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Ranked alternatives
Ordered by Alt Score. Click any score to see the breakdown.
LangGraph is a low-level orchestration framework (by LangChain) for building stateful, multi-agent applications as graphs.
CrewAI is a Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a crew.
Haystack (by deepset) is an open-source framework for building production LLM applications, RAG pipelines and agents.
Mastra is an open-source TypeScript framework for building AI agents, workflows and RAG, from the team behind Gatsby.
Agno (formerly Phidata) is a full-stack Python framework for building multi-agent systems with memory, knowledge and tools.
AutoGen is an open-source Microsoft framework for building multi-agent applications with conversable, collaborating agents.
Semantic Kernel is a Microsoft open-source SDK for integrating LLMs and building AI agents in C#, Python and Java.
The OpenAI Agents SDK is a lightweight, provider-agnostic framework for building multi-agent workflows with handoffs and guardrails.
Pydantic AI is a Python agent framework that brings type-safe, structured outputs and dependency injection to LLM apps.
Feature comparison
Rows come from the AI agent frameworks checklist (17 rows). Human-verified cells only. ? means the value has not been verified.
| AI agent frameworks checklist | LlamaIndex | LangGraph | CrewAI | Haystack | Mastra | Agno |
|---|---|---|---|---|---|---|
| Pricing model | ||||||
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| License | ||||||
| Platforms | ||||||
| Open source | ||||||
| Language (Python) | ||||||
| Language (JS/TS) | ||||||
| Multi-agent orchestration | ||||||
| Graph / stateful workflows | ||||||
| Human-in-the-loop | ||||||
| Streaming support | ||||||
| Built-in memory / state persistence | ||||||
| Tool / function calling | ||||||
| Model-agnostic (multi-provider) | ||||||
| Observability / tracing integration | ||||||
| Managed / hosted deployment | ||||||
| RAG support |
Every fact and feature listed for LlamaIndex is verified against its own pages. Each alternative is sourced on its own page.
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License MIT License verified 2026-07-16
The MIT License
https://raw.githubusercontent.com/run-llama/llama_index/main/LICENSE -
Pricing model OSS + paid hosting verified 2026-07-16
Confirms LlamaIndex/Workflows framework is open source while LlamaParse/LlamaCloud (the credits-based platform on the same pricing page) is paid hosted.
It provides a generous provision of 10k free credits a month to all new users, but is not open source. Our open source projects, LlamaIndex and Workflows, provide AI builders with the foundational bui
https://www.llamaindex.ai/pricing -
Starts at $50/month (LlamaParse Starter) verified 2026-07-16
Cheapest paid LlamaCloud/LlamaParse tier; a $0/month 'Free' tier with 10K credits also exists on the same page.
Starter $50 /month Get started Includes 40K credits Pay-as-you-go up to 400K credits 100 users Basic support
https://www.llamaindex.ai/pricing -
Status active verified 2026-07-16
Release v0.14.23 published 2026-06-24 per the release page's timestamp, and the repository's GitHub API metadata shows pushed_at 2026-07-16 and archived:false, both indicating ongoing active developme
v0.14.23
https://github.com/run-llama/llama_index/releases -
Open source Yes verified 2026-07-16
LlamaIndex OSS (by LlamaIndex) is an open-source framework to build agentic applications.
https://raw.githubusercontent.com/run-llama/llama_index/main/README.md -
Language (Python) Yes verified 2026-07-16
Building with LlamaIndex typically involves working with LlamaIndex core and a chosen set of integrations (or plugins). There are two ways to start building with LlamaIndex in Python:
https://raw.githubusercontent.com/run-llama/llama_index/main/README.md -
Language (JS/TS) Partial verified 2026-07-16
LlamaIndex.TS (npm package 'llamaindex', still published, v0.12.1) provided full JS/TS support historically, but its README now carries a deprecation notice directing users to LlamaCloud/LlamaParse Py
This project is deprecated and no longer maintained.
https://raw.githubusercontent.com/run-llama/LlamaIndexTS/main/README.md -
Multi-agent orchestration Yes verified 2026-07-16
When more than one specialist is required to solve a task you have several options in LlamaIndex, each trading off convenience for flexibility. This page walks through the three most common patterns..
https://developers.llamaindex.ai/python/framework/understanding/agent/multi_agent/ -
Graph / stateful workflows Yes verified 2026-07-16
Workflows are multi-step processes that combine one or more agents, data connectors, and other tools to complete a task. They are event-driven software that allows you
https://developers.llamaindex.ai/python/framework/ -
Human-in-the-loop Yes verified 2026-07-16
Tools can also be defined that get a human in the loop. This is useful for tasks that require human input, such as confirming a tool call or providing feedback.
https://developers.llamaindex.ai/python/framework/understanding/agent/human_in_the_loop/ -
Streaming support Yes verified 2026-07-16
In real-world use, agents can take a long time to run. Providing feedback to the user about the progress of the agent is critical, and streaming allows you to do that.
https://developers.llamaindex.ai/python/framework/understanding/agent/streaming/ -
Built-in memory / state persistence Yes verified 2026-07-16
Memory is a core component of agentic systems. It allows you to store and retrieve information from the past.
https://developers.llamaindex.ai/python/framework/module_guides/deploying/agents/memory/ -
Tool / function calling Yes verified 2026-07-16
The core of expanding agent capabilities is the tools available, and we have good news: LlamaHub from LlamaIndex has hundreds of integrations, including dozens of existing agent tools that you can use
https://developers.llamaindex.ai/python/framework/understanding/agent/tools/ -
Model-agnostic (multi-provider) Yes verified 2026-07-16
LlamaIndex provides a single interface to a large number of different LLMs.
https://developers.llamaindex.ai/python/framework/understanding/using_llms/ -
Observability / tracing integration Yes verified 2026-07-16
LlamaIndex provides one-click observability 🔭 to allow you to build principled LLM applications in a production setting.
https://developers.llamaindex.ai/python/framework/module_guides/observability/ -
Managed / hosted deployment Yes verified 2026-07-16
LlamaParse/LlamaCloud is LlamaIndex's managed hosted offering.
LlamaParse SaaS is hosted on a secure cloud tenant, with data encrypted in transit and at rest.
https://www.llamaindex.ai/pricing -
RAG support Yes verified 2026-07-16
LLMs are trained on enormous bodies of data but they aren’t trained on your data. Retrieval-Augmented Generation (RAG) solves this problem by adding your data to the data LLMs already have access to.
https://developers.llamaindex.ai/python/framework/understanding/rag/
FAQ
Yes. AutoGen, Semantic Kernel and OpenAI Agents SDK have a free tier or are fully free. Free-tier limits in the comparison table are verified and dated.
LangGraph, CrewAI and Haystack — every license claim links its source.