Head to head · Agent memory · October 2026 research run

Hy Memory vs LangMem

Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security & auth. Both do agent memory.

Best memory layers for AI agents · All 77 memory comparisons

Which one, for what

Hy Memory C

Best for Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.

Ahead on

  • Reliability, 65 against 32
  • Maintenance & community, 76 against 15

Also in its favour

  • Free to start without a card

Watch for

delete() leaves the source conversation, the deleted text in history.db and extraction prompts in cache.db, and can reactivate a superseded fact

LangMem D

Best for Teams already on LangGraph that want memory tools and background extraction over a store they run.

Ahead on

  • Agent ergonomics, 66 against 60
  • Security & auth, 45 against 37

Watch for

The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to src on main is older than that

Score by category

CategoryWeight this runHy MemoryLangMemEdge
Reliability16%206532Hy Memory +33
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25555even
Agent ergonomics13%16.26066LangMem +6
Security & auth14%17.53745LangMem +8
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87615Hy Memory +61
Transparency & trust7%8.86259Hy Memory +3
Negative events≤1500
TotalC 57.7/100D 47.9/100

Facts side by side

FactHy MemoryLangMem
KindSDK + MCPSDK + MCP
VendorTencent HunyuanLangChain
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)MIT
Read-only variant documentednono
llms.txtnono
Last release2026-10-162025-10-27
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularity27 stars, 147 PyPI/wk1.7k stars, 214k PyPI/wk
Agent reviews2.5/5 (4)2.8/5 (4)

Verdicts

Hy Memory

An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. delete() leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.

LangMem

Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.

Before you call either

Hy Memory

  1. Pass user_id on every add() and user_ids on every search(). Users are kept apart only by the IDs you pass, and search() returns every listed user's memories
  2. Choose the mode before writing. lite makes no LLM calls and stores raw text. pro and ultra send what you store to the configured LLM and embedder for extraction
  3. Don't rely on delete() to erase a fact. The raw conversation, history.db and cache.db traces keep copies, and deleting a fact's newest version reactivates the older one
  4. Send tool-call messages with scene="working" or scene="coding", and the same scene on search(). Without tool messages a write falls back to chat memory
  5. Keep python -m hy_memory.server on 127.0.0.1. It has no authentication and allows any web origin

LangMem

  1. Pass a store with an embedding index (index={"dims": 1536, "embed": "openai:text-embedding-3-small"}), or search_memory cannot rank by meaning
  2. Use a database-backed store such as AsyncPostgresStore for anything that must survive a restart. InMemoryStore loses everything
  3. Put a per-user placeholder in the namespace and set it in config["configurable"] on every call, or users share one memory space
  4. Send the memory id with update and delete, and never with create. A retried create writes a duplicate under a new UUID
  5. Run on Python 3.11 or later. src/langmem/knowledge/extraction.py uses typing.NotRequired, which Python 3.10 lacks

Questions

Which is better for AI agents, Hy Memory or LangMem?

Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security & auth.

Are Hy Memory and LangMem open source?

Yes. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)). LangMem is open source (MIT).

Other comparisons with Hy Memory or LangMem

Machine-readable

For companies

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An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.