· Jacob
Agent memory that works across every model, and that you own
Model hopping has never been more useful. Use the best model for each job and switch as the leaderboard moves. That only works when your memory travels with you instead of staying locked in one assistant.
Updated · Reviewed by Jacob
Models are becoming commodities. Context isn't.
Every few weeks a different model takes the top of the leaderboard. Anthropic's Opus and Fable, OpenAI's GPT-6 Astra, and Google's Gemini keep trading the lead. Open source models like Llama, Qwen, and DeepSeek are a release or two behind and closing. On everyday work, the gap between the top few is getting hard to notice.
That is good for you. It also changes what is worth holding onto.
The switching cost moved
When one model was clearly ahead, staying put was easy. Now the frontier is a cluster, not a peak, and moving assistants is a quick decision. What makes it feel hard is not capability anymore. It is everything your current assistant knows that a new one would not:
- the conventions in your codebase, and why they exist
- the decisions you already made, and the ones you already ruled out
- how you like work delivered, from format to tone to level of detail
- the people, projects, repos, and accounts you refer to by shorthand
None of that lives in the model. It built up inside one product's private memory, and it does not come with you. Switch tools and you start over, re-explaining things you already said a hundred times.
So the lock-in was never really the model. It is the context, and right now that context sits with whichever vendor you happened to pick.
Portable memory changes who holds the leverage
The fix is not a better private memory feature. It is memory that is not private to any one product: one memory graph that you own, that every assistant can read and write, and that stays with you when you change models.
That is what Agent Memory on Gryz is:
- You own it. Every fact is visible in your dashboard. Edit it, delete it, export it.
- Every assistant shares it. Any MCP client connects to the same store. Claude, Cursor, and anything else that speaks the protocol, including a self hosted open source model behind your own gateway.
- It stays private. Facts belong to your account. They are never used for training and never shown to anyone else.
- It is structured. Small, atomic facts, each attributable. Personal facts follow you everywhere. Project facts are keyed to a repo or workspace.
The interesting part is not that Gryz has a memory feature. It is where the memory lives. When it lives with you, changing assistants costs you almost nothing, you can run several assistants against one shared context instead of three that drift apart, and you can always see what your tools believe about you.
Model hopping is the smart play now
Not long ago, switching models was a project. Now it is often the right call:
- use a top model for hard reasoning
- use a cheap open source model for bulk work
- move the moment a new release changes the math
Hopping is not completely free. Mid project, a new model needs a beat to pick up your context and your task. But that cost keeps dropping, and it is small next to the upside of always using the best tool for the job. The teams that hop freely get better results at a better price. The teams that can't, because their context is stuck in one product, pay to avoid the pain of starting over.
Model hopping has never been more useful, and it only works if the layer underneath is portable. That layer is what Gryz gives you: your memory, your notes, your published docs. One account, every assistant, owned by you. Swap the model on top as often as you like. The part that took months to build stays put.
How to start
You do not need to migrate anything.
- Connect Gryz as an MCP server in Claude, Cursor, or any MCP client. Free with any account.
- Next time you tell an assistant something worth keeping, a preference, a convention, a decision, ask it to remember.
- Recall happens automatically at the start of your next session, in whatever tool you open.
See the Agent Memory overview for scopes and the dashboard, or the Memory API reference to work with it directly.
FAQ
What is agent memory? A store of durable facts an assistant can read and write across sessions, so it does not forget what you told it last time. Gryz makes that store portable across assistants instead of tying it to one product.
How is this different from ChatGPT or Claude memory? Those live inside one product and do not move. Gryz Agent Memory is one graph you own, connected over MCP, that any assistant can read and write. Switching models does not reset what your tools know.
Does it work with open source models? Yes. MCP is an open protocol. Any client that speaks it, including a self hosted open source model behind your own gateway, can read and write the same memory.
Who can see my memories? Only you. Facts are private to your account, visible and editable in your dashboard, and never used for training.
What does it cost? Agent Memory is free with any Gryz account. Higher tiers raise the stored fact and project limits. See pricing.
The best model will keep changing, so hop between them as much as it pays to. The part worth keeping still is what your agents know about you, and that is what Gryz holds.