OpenComputer Review (2026): Pricing, Features & Honest Verdict

OpenComputer gives AI agents a persistent cloud VM instead of a disposable sandbox. Full Linux machine, hardware isolation, checkpoints, hibernation, and a CLI that deploys a prompt as a running agent with a permanent URL. Powerful, and priced by the minute with no free tier. Best for: teams building agent products. Price: from $0.004/min (free plan: no). Rating: 7/10.

What is OpenComputer?

OpenComputer is cloud infrastructure for AI agents, built by Digger and launched publicly in 2026. The argument behind it is straightforward: agents currently run untrusted code inside sandboxes, which are disposable computers that spin up, do a task and disappear. That model was fine when an agent ran a script and exited. It falls apart when an agent needs to remember what it installed yesterday. Every OpenComputer instance is a real virtual machine with its own kernel, filesystem and process space, isolated at the hardware level through KVM, and it stays alive until you stop or delete it.

The second surface is Agent Deploy, which is the piece that got attention on Product Hunt. You install a CLI, run oc agent init, write a prompt in a prompt.md file, and run oc agent deploy. What comes back is a live agent at a permanent HTTP address, backed by durable sessions that survive restarts and can be steered mid-run. It works with Claude Code, Codex, opencode and Cursor. The team includes Utpal Nadiger, Igor Zalutski, Brian Reardon and Mohamed Habib, and they publish a technical blog that is unusually good for a company at this stage, including a piece where they fingerprinted six sandbox providers to compare isolation models.

What Are OpenComputer’s Key Features?

Persistent VMs that do not time out

This is the whole differentiator. Ephemeral sandboxes are stateless, so every session starts from scratch and your agent reinstalls node_modules for the fortieth time because a container timed out. OpenComputer VMs stay on until you explicitly stop them. State survives across sessions with no extra work, no re-provisioning step, and no cold start between agent runs. If you have built anything agentic on top of a sandbox provider, you already know how much code exists purely to rehydrate state that should never have been lost.

Checkpoints you can fork from

Named snapshots, forkable and restorable to any point. Their framing is “git branches for VMs” and it holds up: you can try five approaches in parallel from the same starting point, or roll back a second after an agent corrupts its own environment. For agent work specifically this is more valuable than it is for normal infrastructure, because agents break their environments constantly and the recovery path is usually “delete everything and start again.”

Elastic compute and hibernation

Memory and CPU resize at runtime, from 1 GB up to 16 GB, without restarting the VM. Need more headroom mid-session for a build, then release it after. When you do not need the machine at all, hibernate it and wake it later with state exactly where you left it. You pay only while running. This is the mechanism that makes the per-minute pricing survivable, and it is also the thing you have to actively manage.

A real SDK and CLI surface

TypeScript and Python SDKs, both installable in one line, plus an oc CLI. The docs cover sandbox management, running commands, file operations, mounts, signed preview URLs, interactive terminals, PTY, secrets, templates and webhooks. The durable agent sessions layer adds deployments and revisions, skills, agent URLs, inbound hooks, credentials, GitHub repo events, Slack messaging, schedules and watches. It is a serious API surface. It is also worth noting that a lot of it, including browser sessions, durable agent sessions, usage and reserved capacity, is marked Preview in the documentation.

Agent Deploy: a prompt file becomes a running service

The deployment flow deserves its own mention because of how little ceremony it involves. Install the CLI with a curl script, run oc login, run oc agent init, write what the agent should do in prompt.md, then oc agent deploy and oc agent invoke to smoke test it. What you get back is a permanent HTTP address you can wire into Slack, webhooks or cron. No Dockerfile, no orchestration config, no deciding where the thing lives. The whole setup is designed to be pasted into Claude Code and executed by the agent itself, which is either a clever distribution move or slightly too cute depending on your taste.

How Much Does OpenComputer Cost?

OpenComputer costs $0.004 per minute, which works out to $0.24 per hour or $168.72 per month for a VM left running continuously with 4 GB of memory, 1 vCPU and 20 GB of disk. Memory is adjustable from 1 GB to 16 GB. Disk above the included 20 GB is metered at $0.0000001 per GB-second, roughly $0.26 per GB-month, and that meter runs for the lifetime of the sandbox whether it is running or hibernated. There is no free tier and no trial credit advertised. Custom sizing and volume discounts are available by talking to the team.

That pricing sits awkwardly next to the sandbox providers it is competing with. E2B gives you a Hobby tier with $100 of one-time credits before you pay anything, then $150 per month for Pro on top of usage. Daytona includes $200 of free compute and bills per second at $0.0504 per vCPU-hour plus $0.0162 per GiB-hour. Both let you evaluate for free. OpenComputer asks for a card before you have run a single command, which is a real friction point for the indie developers who read about it on Product Hunt. The per-minute rate itself is reasonable for what you get. The absence of any free allowance is the problem.

Who is OpenComputer Best For?

Use OpenComputer if you are building a product on top of agents and your users need environments that persist between sessions. The company says this directly: it is built for B2B agent platforms, the sort of thing where you are shipping the next Lovable, Devin or Bolt and your users expect their files to still be there tomorrow. Use it if you are running long agent jobs measured in hours or days rather than minutes. Use it if checkpoint-and-fork would let you parallelise work you currently run serially.

Skip OpenComputer if your agent workloads are short and stateless, because you will pay for persistence you are not using and an ephemeral sandbox will be cheaper and simpler. Skip it if you want to evaluate before committing budget, since there is nothing to evaluate on without paying. And be careful if you are a solo developer who forgets to shut things down. A VM left running by accident is $168.72 by the end of the month, and the disk meter keeps ticking even while hibernated.

There is a middle group worth calling out: developers who want one persistent machine for their own agents rather than a fleet for customers. At $168.72 per month for an always-on 4 GB box, you are paying more than a comparable VPS costs, and the things you are paying extra for are checkpoints, forking, runtime resizing and the agent SDK. If you would use those weekly, the premium is fair. If you would use them twice a year, rent a $12 VPS and move on.

Best OpenComputer Alternatives

E2B

The most established name in agent sandboxes, with a $21M Series A and customers including Perplexity, Hugging Face and Manus. The Hobby tier is free with $100 of one-time usage credits, up to 20 concurrent sandboxes and a one hour maximum session length. Pro is $150 per month plus usage, extends sessions to 24 hours and concurrency to 100. E2B wins on maturity and on being free to try. OpenComputer wins on persistence, because E2B sessions still cap out at 24 hours.

Daytona

Pay-as-you-go infrastructure for running AI-generated code, billed per second: $0.0504 per vCPU-hour, $0.0162 per GiB-hour of memory, and 5 GB of storage free before $0.000108 per GiB-hour. GPU instances are available up to an H200 at $4.54 per hour. There is $200 of free compute to start. If your workload is bursty and you want granular billing plus a free runway, Daytona is the easier first step.

Fly.io Machines

Not marketed at agents, but a Fly Machine is a fast-booting VM you can start, stop and keep state on, and plenty of teams already run agent workloads there. You give up checkpoints, forking and the agent-specific SDK surface, and you take on more orchestration yourself. Worth considering if you already run infrastructure on Fly and do not want another vendor.

Final Verdict: Is OpenComputer Worth It?

OpenComputer identified a genuine gap and built the right thing for it. The sandbox model was designed for stateless code execution and agents outgrew it, and nobody else is treating persistence, checkpointing and forking as the primary features rather than the extras. The engineering looks solid, the SDKs and CLI are properly documented, and Agent Deploy turning a prompt.md into a live URL is the cleanest deployment story we have seen for background agents.

What holds the score down is commercial, not technical. No free tier means no evaluation path, which is an odd choice for a developer tool launching on Product Hunt, and it puts OpenComputer at a disadvantage against E2B and Daytona, both of which hand you $100 or $200 of compute to play with. The Preview labels across durable agent sessions, browser sessions and reserved capacity mean the newest features are not yet load-bearing. Our recommendation: if you are a company building an agent product and persistent state is costing you engineering time today, talk to them and start a pilot. If you are an individual developer curious about deploying an agent, start on a provider with a free tier and come back when the bill would be justified. Rated 7 out of 10.