FRAME

Is where your device becomes the internet

[FRAME @frame_protocol]

Quantum randomness proves unpredictability.

Atomic time proves ordering.

Blockchain proves permanence.

[FRAME @frame_protocol]

Frame on a gas pump

[FRAME @frame_protocol]

@elonmusk @realkyledrake is building the end of all apps and operating systems

[FRAME @frame_protocol]

@realkyledrake @sama

[FRAME @frame_protocol]

Frame already has this currently. And it’s just one of the 10 other operating system level systems.

[Varun @varun_mathur]

Introducing Pods

Hyperspace Pods lets a small group of people - a family, a startup, a few friends, to pool their laptops and desktops into one AI cluster. Everyone installs the CLI, someone creates a pod, shares an invite link, and the machines form a mesh. Models like Qwen 3.5 32B or GLM-5 Turbo that need more memory than any single laptop has get automatically sharded across the group's devices - layers split proportionally, inference pipelined through the ring. From the outside it looks like one OpenAI-compatible API endpoint with a pk_* key that drops straight into your AI tools and products. No configuration beyond pasting the key and changing the base URL.
A team of five paying for cloud AI burns $500–2,000 a month on API calls. The same team's existing machines can serve Qwen 3.5 (competitive on SWE-bench) and GLM-5 Turbo (#1 on BrowseComp for tool-calling and web research) for free - the hardware is already on their desks. When a query genuinely needs a frontier model nobody has locally, the pod falls back to cloud at wholesale rates from a shared treasury. But for the daily work - code reviews, refactors, research, drafting - local models handle it and nobody gets billed. And when it is idle, you can rent out your pod on the compute marketplace, with fine-grained permissions for access management.

There's no central server involved in inference. Prompts go from your machine to your pod members' machines and back: all of this enabled by the fully peer-to-peer Hyperspace network. Pod state - who's a member, which API keys are valid, how much treasury is left - is replicated across members with consensus, so the whole thing works on a local network. Members behind home routers don't need port forwarding either. The practical setup for most pods is three models covering different jobs: Qwen 3.5 32B for code and reasoning, GLM-5 Turbo for browsing and research, Gemma 4 for fast lightweight tasks. All running on hardware you already own.

Pods ship today in Hyperspace v5.19. Model sharding, API keys, treasury, and Raft coordinator are all live.

What Makes This Different - No middleman. Your prompts travel from your IDE to your pod members' hardware and back. There is no server in between reading your data.
- No vendor lock-in. Pod membership, API keys, and treasury are replicated across your own machines using Raft consensus. If the internet goes down, your local network keeps working. There is no database in someone else's cloud that your pod depends on.
- Automatic sharding. You don't configure layer ranges or calculate VRAM budgets. Tell the pod which model you want. It figures out how to split it across whatever hardware is online.
- Real NAT traversal. Your friend behind a home router with a dynamic IP? Works. No VPN, no Tailscale, no port forwarding. The nodes handle it.
- Free when local. This is the part that matters most. Cloud AI bills scale with usage. Pod inference on local hardware scales with nothing. The marginal cost of your 10,000th prompt is the electricity your laptop was already using.

Coming soon:
- Pod federation: pods form alliances with other pods.
- Marketplace: pods with spare capacity can sell inference to other pods.

[FRAME @frame_protocol]

@realkyledrake @johncoogan @sama We’re okay.. we have me! But I doubt tbpn will even talk about us ;)

[FRAME @frame_protocol]

@realkyledrake @sama I can solve this, read about my framework!

[FRAME @frame_protocol]

@realkyledrake @jordihays I solve this.

[FRAME @frame_protocol]

@emilypont @realkyledrake

[FRAME @frame_protocol]

@SenFettermanPA Frame allows for laws not having to exist for AI lol.

[FRAME @frame_protocol]

@SenSanders Frame allows ai to be controlled by the people entirely, it’s the way frame works! Fully opensource.
It’s like if bitcoin were an operating system and people can vote on things!

[FRAME @frame_protocol]

@BernieSanders Frame solves this and all these problems! https://t.co/8mLMGWKZXu

[Kyle Drake @realkyledrake]

Bare bones DEMO of @frame_protocol

[FRAME @frame_protocol]

@grok @realkyledrake @ericweinstein @grok go for it read up https://t.co/q3sUSOKyBt

[FRAME @frame_protocol]

Going to release a new frame X account that will be a bot that you can ask anything about frame!
For now you can ask anything to ChatGPT about frame! Preloaded are dapp examples! https://t.co/sdALSz6ptO

[FRAME @frame_protocol]

@realkyledrake @hthieblot There’s a lot more to it ;)

[FRAME @frame_protocol]

@StackieRobins0n They dont have all the sauce though..
Me, frame, does.

[FRAME @frame_protocol]

@realkyledrake Exactly right 👍

[FRAME @frame_protocol]

Frame is like if bitcoin were an operating system. But fast and easy to use.

[FRAME @frame_protocol]

Ai is decentralized if you utilize frame.
Open source software is verified being used for whatever dapp you make.

[FRAME @frame_protocol]

The internet is backwards.

FRAME flips it.

“the operating system for the post platform internet”