# Mem0 Python SDK v2.2.1: what's new, verdict & setup Canonical: https://theagenticweekly.com/tools/mem0 · Released: 2026-09-25 · Last verified: 2026-10-26 · Evidence: Tested (smoke test, 2026-10-26, local 3B model plus a local embedder) · Vendor: Mem0 · Official site: https://mem0.ai/ > Open-source and hosted memory layer that lets agents remember users across sessions, with a free tier and published request quotas. ## Verdict **Open-source and hosted memory layer that lets agents remember users across sessions, with a free tier and published request quotas.** Good for: - Apps that need long-term per-user memory Skip if: - You only need a vector database Tested. Tested 2026-10-26 (America/Chicago). Mem0's open-source SDK 2.2.1 stored a fact from one chat message with a local 3B model and retrieved it with a semantic search (2.04 s) on the second attempt; the first two runs failed on a missing package and an API change. Test environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key. The models were local (Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11 for memory extraction; nomic-embed-text v1.5 (Q4_K_M, through Ollama) for embeddings); we tested the tool, not any vendor's hosted models. Not tested: Mem0's hosted platform, pricing tiers and quotas: only the open-source SDK was run; Graph memory, multi-user isolation, updates and deletes, and the optional extras (spaCy, fastembed); Retrieval quality over more than one fact: a single message and a single query is a smoke test, not a benchmark; Timing: add() ran while another model job loaded the machine. These are smoke tests, not a benchmark. Full log: /tests/mem0. Test scope: - Kind and date: smoke test, 2026-10-26 (America/Chicago). Not a benchmark. - What we ran: Mem0's open-source SDK 2.2.1 stored a fact from one chat message with a local 3B model and retrieved it with a semantic search (2.04 s) on the second attempt; the first two runs failed on a missing package and an API change. - Model used: Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11 for memory extraction; nomic-embed-text v1.5 (Q4_K_M, through Ollama) for embeddings - Environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key - Not tested: Mem0's hosted platform, pricing tiers and quotas: only the open-source SDK was run; Graph memory, multi-user isolation, updates and deletes, and the optional extras (spaCy, fastembed); Retrieval quality over more than one fact: a single message and a single query is a smoke test, not a benchmark; Timing: add() ran while another model job loaded the machine. Full test log (commands, versions, raw output): [Mem0 mem0ai 2.2.1 (open-source Python SDK): our test log](https://theagenticweekly.com/tests/mem0) Pricing: Official page, dated. Read from mem0.ai/pricing on 2026-10-25. (checked 2026-10-25) ## Best for - [Best AI tool for agent building](https://theagenticweekly.com/best/agent-building) (#-): Memory layer API for agents and apps. ## Key facts Mem0's pricing page lists Free (10,000 add requests and 1,000 retrieval requests a month), $19 a month (50,000 add and 5,000 retrieval) and $249 a month (500,000 add and 50,000 retrieval), plus Enterprise. The repository is Apache-2.0 and the Python SDK v2.2.1 was tagged Sep 25, 2026. - License: Apache-2.0 (per GitHub) - Platforms: API, Python and JS SDKs, open-source self-host - Pricing model: Freemium - Free tier: Free: 10,000 add requests and 1,000 retrieval requests per month - Paid plans: $19 per month (50,000 add / 5,000 retrieval); $249 per month (500,000 add / 50,000 retrieval); Enterprise custom - GitHub: mem0ai/mem0: 67,804 stars on 2026-10-25, last push 2026-10-23 - Latest release we saw: Python SDK v2.2.1, 2026-09-25 - How to start: Create an API key at mem0.ai or install the open-source package and call add and search. - Python SDK v2.2.1 (2026-09-25): the newest release listed on the official page or repository when we read it on 2026-10-25. ## How to set it up: Get started with Mem0 These steps come from the vendor's own pages as read on 2026-10-25. We have not run Mem0. 1. **Get access.** Create an API key at mem0.ai or install the open-source package and call add and search. 2. **Check the limits and costs first.** Free: 10,000 add requests and 1,000 retrieval requests per month. Paid: $19 per month (50,000 add / 5,000 retrieval); $249 per month (500,000 add / 50,000 retrieval); Enterprise custom. Read from mem0.ai/pricing on 2026-10-25. ## Pros and cons Pros: - Published quotas - Open-source option Cons: - Add and retrieval quotas are separate ## Alternatives - [Letta](https://theagenticweekly.com/tools/letta): Platform and open-source framework for stateful agents that keep and improve memory across sessions. - [LangGraph](https://theagenticweekly.com/tools/langgraph): Low-level framework for building long-running, stateful agents as graphs. - [Langflow](https://theagenticweekly.com/tools/langflow): MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following. - [Botpress](https://theagenticweekly.com/tools/botpress): Customer-support AI agent platform with a free plan and conversation-based paid plans. - [Gumloop](https://theagenticweekly.com/tools/gumloop): Agent builder for teams; plans start at $37 per month with 20k included credits. - [Lindy](https://theagenticweekly.com/tools/lindy): AI 'employee' builder that connects to your tools; Free plan with $50 in credits that last 7 days, then credit-based plans. - [Microsoft Copilot Studio](https://theagenticweekly.com/tools/copilot-studio): Microsoft's platform for creating and managing custom agents, workflows and apps with no code. - [Pydantic AI](https://theagenticweekly.com/tools/pydantic-ai): Python agent framework built on Pydantic types, covering agents, realtime voice, image generation and embeddings. - [Relevance AI](https://theagenticweekly.com/tools/relevance-ai): Platform for specialist AI agents for sales, customer success, marketing and HR, with an embedded deployment team. - [Voiceflow](https://theagenticweekly.com/tools/voiceflow): Platform for chat and voice AI agents for customer experience teams. - [Vercel AI SDK](https://theagenticweekly.com/tools/vercel-ai-sdk): Vercel's TypeScript SDK that gives one API across many model providers, with streaming and agent helpers. - [Agno](https://theagenticweekly.com/tools/agno): Open-source agent framework that now sells a self-driving agent platform you run in your own cloud. ## FAQ ### What is Mem0? Mem0's pricing page lists Free (10,000 add requests and 1,000 retrieval requests a month), $19 a month (50,000 add and 5,000 retrieval) and $249 a month (500,000 add and 50,000 retrieval), plus Enterprise. The repository is Apache-2.0 and the Python SDK v2.2.1 was tagged Sep 25, 2026. ### Is Mem0 free? Free: 10,000 add requests and 1,000 retrieval requests per month. Paid: $19 per month (50,000 add / 5,000 retrieval); $249 per month (500,000 add / 50,000 retrieval); Enterprise custom. Read from mem0.ai/pricing on 2026-10-25. Checked 2026-10-25; prices change, so confirm on the vendor's page. ### What license is Mem0 under? Its license: Apache-2.0 (per GitHub). Read from the project's own pages on 2026-10-25. ## What we have not verified - Benchmark claims (vendor) ## Sources - [Mem0](https://mem0.ai/) (fetched 2026-10-25) - [Mem0 pricing](https://mem0.ai/pricing) (fetched 2026-10-25) - [Mem0 repository (GitHub)](https://github.com/mem0ai/mem0) (fetched 2026-10-25) ## How to cite Agentic Weekly, "Mem0 Python SDK v2.2.1: what's new, verdict & setup", last updated 2026-10-26, https://theagenticweekly.com/tools/mem0 Keep the Reported or Tested label when you quote the verdict.