jurniti vs OpenComputer: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of jurniti and OpenComputer — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

jurniti

Paid

Managed 24/7 hosting for coding agents, each running in its own Firecracker microVM with your own model keys and no token markup.

Firecracker microVM Isolation: Every agent runs in its own KVM-backed virtual machine with hardware-enforced tenant isolation instead of a shared-kernel container.
Bring Your Own Key: OpenRouter, OpenAI or Anthropic keys live only inside the customer's VM — jurniti never sees them, never proxies calls and never marks up model spend.
Multi-Harness Support: Runs Claude Code, Codex CLI, OpenClaw, Hermes, OpenCode, Devin CLI, Mastra and Pi, each in its own dedicated microVM.
Fleet CLI: A jurniti command-line tool to boot agents, list fleet status, dispatch work and copy results back, so the whole fleet is managed from a terminal.
Swarm Runtime: Boots dozens of isolated microVM workers at once and dispatches the same brief to every worker, with results collected in a single command.
Flat Per-VM or Hourly Billing: A flat monthly or annual price per agent VM, or per-second metered On-Demand and Spot pricing for bursty workloads, with prepaid credits.
Automated Provisioning: Payment triggers a magic-link sign-in and an auto-provisioner that has a live microVM running in about three minutes with no human in the loop.
Custom Subdomain and Sidecars: Pro tiers add a custom subdomain, alongside separate microVM services for multi-agent communication and long-term agent memory.

Always-On Coding Agents: Keeping a Claude Code or Codex agent working on a backlog overnight without leaving a laptop running.
Secure Key Handling: Running agents for a team that cannot let model API keys leave its own infrastructure boundary.
Parallel Agent Fleets: Dispatching one brief to fifty isolated workers to compare approaches or parallelize a large refactor.
Bursty Batch Work: Using per-second Spot or On-Demand VMs for agents that only run a few hours a day, paying only for active runtime.
Self-Hosting Alternative: Replacing hand-rolled VPS setups for open-source agent harnesses like Hermes, OpenClaw or OpenCode.
Long-Running Agent Memory: Pairing an agent VM with a dedicated memory microVM so knowledge persists between sessions.

Digger

Freemium

Background agent cloud that runs TypeScript agents on hardware-isolated Linux microVMs, with secrets the agent never sees.

Agent as a TypeScript Function: Declare a model, tools and MCP servers inside one exported function and deploy it live with `opencomputer deploy` — the platform owns the agent loop, sessions, streaming and versions.
Full Linux MicroVM Per Session: Each run gets a real machine with bash, a read-write filesystem, apt/npm/pip package installs and full network egress, isolated at the hardware level via KVM.
Durable Steerable Sessions: Runs stream to the client, accept mid-run steering, hibernate automatically when idle and resume exactly where they left off instead of restarting.
Origin-Bound Secret Injection: Secrets are defined per connection and injected only after a request leaves the sandbox, so the agent can act with a token it can never read or exfiltrate.
Checkpoint and Fork: Named snapshots work like git branches for VMs — fork a prepared machine to try five approaches in parallel, or restore one at any time.
Scheduled Autonomous Runs: A `defineSchedule` cron entry keeps a deployed agent running on its own, with sessions, streaming, MCP and Slack delivery handled by the platform.
Model-Agnostic Passthrough: The model is just a string that can change per request; token usage is passed through at raw API rates with no markup, or drops to zero with your own key or subscription.
Bare Sandboxes API: `Sandbox.create()` exposes the same microVMs directly — checkpoint, fork and live resize — for teams that want to bring their own harness and own the loop.

Codebase Hygiene Bots: Deploy an agent that finds stale feature flags still referenced in code and opens a cleanup pull request for each one on a weekday schedule.
Background Coding Agents: Hand off long refactors or migrations to an agent that clones the repo, runs the test suite in a real shell and works while you sleep.
Media and Data Pipelines: Run agents that need heavyweight binaries such as ffmpeg or headless Chromium, which serverless function runtimes cannot host.
Parallel Approach Exploration: Checkpoint a machine once the environment is prepared, then fork it to evaluate several agent strategies from an identical starting state.
Safe Third-Party API Automation: Let an agent operate on GitHub, Slack or an internal API through origin-bound credentials it is structurally unable to read or redirect.
Custom Agent Harness Hosting: Use the bare sandbox API as compute for an in-house agent framework, keeping your own loop while outsourcing VM lifecycle and scaling.