Oil has a price. Gold has a price. Compute doesn't.
Every serious market has a number you can look up - compute has nowhere.
Nobody else offers the full stack.
Compute market, cloud, AI platform, operating system and hardware - everyone else owns a piece.
Your stuff. Not ours. Move anywhere, anytime.
Run it locally, move it anywhere, and take everything you built with you.
Ownership = control + portability + optionality.
Fourteen things you accumulate, and a tilde means a download that will not run anywhere else.
The model gets cheaper. Your intelligence gets bigger.
The price of a model falls every quarter, but five years of your memory and decisions does not.
Ask AWS about data centres and you get AWS's data centres.
Squares drawn to area, and they each see one fleet - their own.
Earth Compute can tell you if you're getting ripped off.
Your bill against every provider running the same machine, twelve months.
Where is an H100 cheapest on Earth?
The same GPU, the same hour, priced in every region we index.
The wrong provider decision compounds every hour.
Hyperscaler list price against the cheapest qualified machine across thirty-four providers, over a thousand GPU-hours.
Every job teaches the router.
Which model, which hardware, how fast, how often it failed, what it cost - operational telemetry, not personal content.
First, we mapped out the entire world's data centres and GPUs.
Earth Compute is the intelligence layer for the physical infrastructure powering AI. Data centres, cloud regions, GPU clusters, bare metal, internet exchanges, fibre routes and subsea cables in one connected view - with pricing, availability and history running from early infrastructure through to projects planned for 2030. It is available as an API, so applications, analysts and agents can query the physical market directly.
The moat is not collecting prices - it is normalising millions of inconsistent listings into genuinely comparable infrastructure. A provider knows its asking price. Earth Compute knows the market price: whether a configuration is unusually expensive, whether another region offers better value, whether supply is tightening, and whether the advertised specification is really equivalent. Competitors cannot buy the historical record; it only accrues by observing the market for years.
Product mix
Feed freshness
Index summary
| Facilities | 7,369 |
| Countries | 60 |
| Products | 32,324 |
| Feeds | 39 |
Then, we connected them to create an Airbnb of cloud.
OwnCloud puts hyperscalers, regional clouds, GPU operators and bare metal providers behind one search, purchase and deployment layer. The workload is described by requirement - CPU, GPU, memory, region, latency, sovereignty, budget, interruption policy - and infrastructure that cannot meet it is removed before price is compared. Agents and applications can transact through the same API, with stablecoin payments, so software can buy its own infrastructure inside limits the owner sets.
Two network effects run in opposite directions: more providers give customers better selection, and more customer demand gives providers better utilisation. Underneath both, OwnCloud observes what providers actually deliver - provisioning time, real uptime, sustained throughput, failure frequency, cancellation behaviour - rather than what they promise. That machine-observed reputation record cannot be replicated by a new entrant without the same years of history.
Capacity indexed
Reach
| Providers | 32 |
| Regions | 482 |
| Countries | 60 |
| Products | 32,324 |
Payment options
| Card | ✓ |
| Stablecoin | ✓ |
| Agent wallet | ✓ |
| Reserved | ✓ |
One cloud over many clouds.
Booking.com for compute - compare thousands of options without visiting thousands of pages.
Host, train and run models up to 80% less.
The same workload, priced across every provider we index.
Major breakthroughs in cost reduction.
One open model in four places, where only the location changes.
Then, we built a platform to host the latest open-source models.
OwnAI runs the latest open-weight models across text, images, video, voice, music, coding, research, documents, analysis and agents. A single request can become a multi-model workflow - one model researches, another reasons, another generates, another verifies - returning one finished result. The user chooses where it executes: on Own 1, on their own infrastructure, or on OwnCloud.
Every model company can show benchmarks where its own model wins. OwnAI measures models against real tasks and learns which is genuinely right for each job - which is unnecessarily expensive, which smaller model performs equally well, which needs the fewest retries. The unit that matters is not token price but cost per successful outcome: a model that costs half as much and fails three times is not cheaper. As prices, limits and quality shift, OwnAI re-routes - smart order routing, applied to intelligence.
OwnAI vs the AI subscriptions people already pay for
| Capability | OwnAI | ChatGPT | Claude | Gemini | Grok | HeyGen |
|---|---|---|---|---|---|---|
| Choose the model per task | ● | ◐ | ◐ | ◐ | ◐ | ○ |
| Choose where it runs | ● | ○ | ○ | ○ | ○ | ○ |
| Run fully offline / on-device | ● | ○ | ○ | ○ | ○ | ○ |
| Open-weight models | ● | ○ | ○ | ○ | ○ | ○ |
| Text · image · video · voice · code in one place | ● | ◐ | ◐ | ◐ | ◐ | ○ |
| Multi-model workflow in one request | ● | ◐ | ◐ | ◐ | ○ | ○ |
| No per-seat lock-in to one vendor's models | ● | ○ | ○ | ○ | ○ | ○ |
Cost cascade
Subscription tiers
| Go | $8 |
| Pro | $12 |
| Max | $50 |
| Own 1 owner | local |
Execution zones
| Own 1 | private |
| Your infra | sovereign |
| OwnCloud | scale |
Modalities
| Chat · Code · Agents | 3 |
| Image · Video | 2 |
| TTS · STT | 2 |
Ten kinds of intelligence. One workspace.
Chat, text, reasoning, coding, research, image, video, voice, music and agents - behind one experience.
Why should seven kinds of AI require seven products?
Nine capabilities across six platforms, where only one row runs all the way.
A new billing system for AI. Unlimited time-based access.
Unlimited time-based access, against two or three separate meters you cannot see.
One bill. Many functions. Unlimited tokens.
Six subscriptions to cover one workflow, or one that covers all of it.
Many AI subscriptions add up over time.
The annual difference becomes real when you stop buying a separate premium tool for every job.
A new breakthrough in AI privacy.
Where the work runs, who controls it, who keeps the memory, and whether it can leave.
| Brand | Local route | User control | Memory | Portability | Overall |
|---|---|---|---|---|---|
| OAOwnAI | 9/10 | 9/10 | 9/10 | 9/10 | 9.0 |
| CLClaude | 5/10 | 3/10 | 3/10 | 2/10 | 3.3 |
| PPPerplexity | 4/10 | 3/10 | 4/10 | 2/10 | 3.3 |
| GPChatGPT | 4/10 | 3/10 | 3/10 | 2/10 | 3.0 |
| GEGemini | 4/10 | 3/10 | 3/10 | 2/10 | 3.0 |
| GKGrok | 4/10 | 3/10 | 3/10 | 2/10 | 3.0 |
Then, we built an operating system to run it all efficiently.
OwnOS is a lightweight, open-source operating system designed for models and agents rather than retrofitted for them. Built on NixOS with TPM2-protected keys, Btrfs snapshots, atomic updates, ERC-4337 smart accounts and x402 machine payments. Every model, application and agent inherits ten native systems: identity, permissions, memory, data access, wallet, budget, payment policy, usage metering, audit history and compute routing.
The moat is not a permission screen - it is the policy and behaviour graph underneath it. OwnOS learns which actions are normal for each kind of agent, which sequences are dangerous, which spending limits fit, and when a human must approve. It also records how autonomous systems fail: what was attempted, which permission was violated, what changed, how the environment was restored, and which policy prevents recurrence. Every failure teaches the system how to protect the next agent.
Declarative NixOS base with atomic updates. Resources go to models, not to the desktop.
Local models, vector storage, private memory and up to eight agents as first-class OS services.
Auditable, forkable, portable. No dependency on a vendor's continued goodwill.
TPM2-protected keys, containerised execution, Btrfs snapshots and one-command rollback.
OwnOS vs existing operating systems
| Capability | OwnOS | Windows | macOS | ChromeOS | Ubuntu | NixOS |
|---|---|---|---|---|---|---|
| Agent identity as an OS primitive | ● | ○ | ○ | ○ | ○ | ○ |
| Per-agent budgets and spending limits | ● | ○ | ○ | ○ | ○ | ○ |
| Native wallet and machine payments | ● | ○ | ○ | ○ | ○ | ○ |
| Atomic snapshots and rollback | ● | ◐ | ◐ | ◐ | ◐ | ● |
| Declarative, reproducible configuration | ● | ○ | ○ | ○ | ○ | ● |
| Local model runtime built in | ● | ○ | ◐ | ○ | ○ | ○ |
| Audit trail for every machine action | ● | ◐ | ◐ | ◐ | ◐ | ◐ |
| Open source | ● | ○ | ○ | ◐ | ● | ● |
Ten native systems
| Identity · Permissions | 2 |
| Memory · Data access | 2 |
| Wallet · Budget · Policy | 3 |
| Metering · Audit · Routing | 3 |
Agent permission example
| Budget | 50 USDC/mo |
| Per transaction | 5 USDC |
| Expires | 30 days |
| Services | 3 approved |
Security stack
| TPM2 keys | ✓ |
| Containers | ✓ |
| Snapshots | ✓ |
| Atomic update | ✓ |
Built for AI agents. Not just desktop apps.
Ten things an operating system needs once software starts acting on its own.
Agents can safely work with money.
You set the budget and the machine enforces it, which makes agents economically native.
Secure by design.
OwnOS gives users control without sacrificing security.
Build once. Run anywhere. Move anytime.
Everything you built comes with you - try exporting it anywhere else.
AWS on Monday. Hetzner on Tuesday. Korea on Wednesday.
Same agents, same memory, same history, same permissions, wherever it runs.
Then, we put it in your hands.
Own 1 is a personal AI computer. It runs two compatible local models simultaneously alongside vector storage, private memory, voice services and up to eight specialised agents coordinated by a SuperAgent - on a fanless machine that sits on a desk. Up to five people reach it from their phones, so a family or a team shares one device. Sensitive work never leaves it. Beyond electricity there are no API bills and no credits to run out of, and when a job genuinely needs more, it bursts to OwnCloud under rules the owner sets.
Own 1 decides what should stay personal - weighing privacy sensitivity, model size, local hardware, cloud price, latency, energy and budget to determine whether a task can leave the device at all. Over time it builds a Personal Intelligence Profile that lives locally: context, working style, tools, documents, workflows, agent history and trusted relationships. The more it learns, the more useful it becomes, without any of it accumulating in a central surveillance dataset. That is a product moat and a trust moat at once.
One place on the device to install models, agents, skills, MCPs, data sets and dev tools - local first, with API options where they make sense.
Latency, before → after
Tokens/sec, before → after
Run outcomes
Benchmark scope
| Runs | 1,224 |
| Models | 44 |
| Modalities | 7 |
| Days | 55 |
Video on integrated GPU
Specification
| CPU | Ultra 9 285H |
| GPU | Arc 140T |
| RAM | 96 GB |
| Price | TBC |
Private AI you own, in four numbers.
Agents, apps, storage and speed - all of it running on the box on your desk.
31 days of optimisation. 812 measured runs.
Same hardware throughout, so every gain came from software we wrote.
Twelve full-time AI employees. 24/7. On one box.
Twelve kinds of work a business pays for, on one machine that never stops.
Productivity and economics.
Twelve roles at a blended $85,000 against one machine and its electricity.
One box. Up to ten people.
A household, a studio or a small team all work off the same machine at once.
From three people up, it pays for itself inside the year.
$4,000 once and about $8 a month after that, which a single light user should not buy.
Major breakthroughs in cost reduction.
One open model, four places to run it. Only the location changes.
Ask AWS about data centres and you get AWS's data centres.
Squares drawn to area. They each see one fleet - their own.
AWS on Monday. Hetzner on Tuesday. Korea on Wednesday.
Same agents, same memory, same history, same permissions. Your stuff moves with you.
OwnCloud + OwnAI = the whole set.
34 providers, open weights, three execution zones. Everyone else gives you one of each.
We mapped the world's compute. Connected its infrastructure. Built intelligence above it. Gave it rules. And put it in your hands.