LlamaIndex vs Mem0
Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.
Direct Answer
LlamaIndex suits teams needing open-source access, data framework focus, and 51,792 GitHub stars in current listing data. Mem0 suits teams needing freemium $49/mo, memory focus, and 63,787 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.
What this comparison weighs
- Pricing and free-tier availability
- License model and deployment fit
- GitHub adoption and contributor depth
- Catalog tags, integrations, and supported workflows
| Metric | LlamaIndex | Mem0 |
|---|---|---|
| GitHub Stars | 51.8K | 63.8K |
| Contributors | 475 | 393 |
| Last Commit | Aug 20, 2026 | Aug 21, 2026 |
| Open Issues | 651 | 683 |
| License | open-source | open-source |
| Pricing | open-source | freemium |
| Free Tier | Yes | Yes |
| Category | dev-tools | dev-tools |
| Trending | No | No |
Choose LlamaIndex if you need
- • LlamaIndex stands out for Data Framework workflows that are not listed for Mem0.
- • LlamaIndex is the stronger pick when Gemini matters because that capability is listed only on its profile.
- • LlamaIndex has a larger visible contributor base (475 vs 393).
Choose Mem0 if you need
- • Mem0 stands out for Memory workflows that are not listed for LlamaIndex.
- • Mem0 is the stronger pick when Langchain matters because that capability is listed only on its profile.
- • Mem0 shows broader GitHub adoption with 63,787 stars versus 51,792 for LlamaIndex.
Meaningful differences
- • Pricing model: LlamaIndex is listed as open-source, while Mem0 is listed as freemium from $49/mo.
- • Workflow emphasis: LlamaIndex highlights Data Framework, while Mem0 highlights Memory.
- • GitHub adoption: LlamaIndex shows 51,792 stars versus 63,787 for Mem0.
- • Contributor count: LlamaIndex lists 475 contributors and Mem0 lists 393.
Shared capabilities
- • Agents
- • Open Source
- • Openai
- • Anthropic
Shared Tags
Only in LlamaIndex
Only in Mem0
Limitations and evidence
- • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
- • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
- • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.
About LlamaIndex
LlamaIndex is the leading data framework for building LLM-powered applications. Provides data connectors for 160+ sources, advanced RAG pipelines, document agents, and a workflow engine for complex agentic applications. The standard for connecting LLMs to your data.
View full listingAbout Mem0
Mem0 provides a managed memory layer that gives AI agents and chatbots the ability to remember user preferences, past interactions, and contextual facts across sessions. It automatically extracts and stores relevant memories from conversations, retrieves them at inference time via semantic search, and handles forgetting of stale information. Compatible with any LLM and easy to self-host, Mem0 is the most widely adopted open-source memory solution for AI applications.
View full listing