StereOS is live · free · last verified 8 Nov 2026 · viability monitor
StereOS
Run AI coding agents inside disposable, fully isolated Linux VMs with the masterblaster CLI.
StereOS earns its place when an AI coding agent needs a real kernel boundary and hardware access — secure boot, FIPS, GPU passthrough — not just a namespace. Full VMs give separation Docker plus gVisor and Firecracker-style microVMs don't match, and nested virtualization lets an agent run Kubernetes inside its own box. The trade-off is CLI-only, jcard.toml-driven tooling, so adopt it because the isolation requirement is real, not because it's convenient.
Verdict generatedVerified 6d ago · liveness 66/100 · cite: rightaichoice.com/tools/stereos
- Security teams that need kernel-level isolation for AI coding agents, not container namespaces
- Self-hosted enterprise deployments running on bare metal
- Developers running local models on GPUs via ollama or vLLM inside a sandbox
- Platform engineers who need agents to run Kubernetes or docker compose inside their own VM
- Anyone who wants a GUI or web console — the whole workflow is the mb CLI
- Beginners unfamiliar with Linux, terminals, or VM concepts
- Teams that only need light isolation and would be happier with Docker plus gVisor
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Skip StereOS if you want a GUI or web console, are uncomfortable living in a terminal with jcard.toml files, or only need light isolation that Docker plus gVisor already covers.
Each sandbox is a full VM, not a container, so RAM, disk, and CPU overhead per agent is significantly higher than Docker plus gVisor — budget host resources accordingly
StereOS is Apache 2.0 and free to run, so the real cost is the hardware and operator time it consumes. Budget for a capable Linux host — ideally bare metal with a GPU if you want local-model passthrough — plus the engineering hours to learn the mb CLI and jcard.toml. That makes it cheaper on paper than commercial agent sandbox platforms that charge per seat or per agent-hour, but it's a bring-your-own-hardware proposition rather than a turnkey hosted service.
In short
StereOS — Run AI coding agents inside disposable, fully isolated Linux VMs with the masterblaster CLI. Best for Security teams that need kernel-level isolation for AI coding agents, not container namespaces, Self-hosted enterprise deployments running on bare metal, Developers running local models on GPUs via ollama or vLLM inside a sandbox. Free to use.
What is StereOS?
StereOS — Run AI coding agents inside disposable, fully isolated Linux VMs with the masterblaster CLI. Best for Security teams that need kernel-level isolation for AI coding agents, not container namespaces, Self-hosted enterprise deployments running on bare metal, Developers running local models on GPUs via ollama or vLLM inside a sandbox. Free to use.
StereOS is an open-source Linux OS built for one job: running AI coding agents inside disposable sandboxed VMs so they never touch your host machine. The masterblaster (mb) CLI installs with a curl one-liner, mb serve keeps a daemon running to manage VM processes, and mb pull grabs a pre-built VM image — a Mixtape — with agents already inside, such as opencode-mixtape. A jcard.toml in your working directory declares which mixtape to boot and which agent harnesses to launch with what prompt. mb up boots the VM, mb ssh drops you inside, and mb down plus mb destroy clean up. The design choice is deliberate: full virtual machines, not containers or microVMs. Every agent gets its own kernel, RAM, disk, and network, with nothing shared back to the host. That buys hardware reach containers can't offer — secure boot, FIPS compliance, GPU passthrough for local models via ollama or vLLM, and bare-metal deployment rather than KVM only. Nested virtualization works too, so an agent can run Kubernetes, docker compose, or kick off other agents inside its own VM without an external platform. The audience is a developer or platform team with a real isolation requirement: self-hosted setups, bare-metal enterprise fleets, or anyone uneasy about handing a coding agent host-level access. Inspection commands (mb list, mb status, mb mixtapes) keep sandboxes visible, and anonymous telemetry can be switched off with the global --disable-telemetry flag. The whole workflow is terminal-based — mb plus jcard.toml, no GUI or web console. Against Docker plus gVisor, stereOS is heavier per agent but reaches kernel-level separation and hardware access those stacks don't. Compared with microVM tooling like Firecracker or Cloud Hypervisor, the argument is that stripped virtual hardware means no secure boot, no FIPS, no GPU passthrough, and shaky boundaries for nested virtualization. Pick it when the isolation requirement is genuine and your team lives in a shell.
Key features
- Run AI coding agents inside disposable sandboxed Linux VMs
- Full VM isolation — each agent gets its own kernel, RAM, disk, and network
- masterblaster (mb) CLI for install, sandbox lifecycle, and inspection
- Install via curl one-liner from mb.stereos.ai
- Pre-built Mixtape VM images with agents included (mb pull)
- jcard.toml configuration for choosing mixtape and agent harnesses (mb init)
- Boot and connect to a sandbox with mb up and mb ssh
- Tear down sandboxes with mb down and mb destroy
- Daemon mode via mb serve to manage VM processes
- Inspect sandboxes with mb list, mb status, and mb mixtapes
- Secure boot and FIPS compliance inside the VM
- GPU passthrough for local models via ollama or vLLM
- Bare-metal deployment, not just KVM
- Nested virtualization — run Kubernetes or docker compose inside the VM
- Global --disable-telemetry flag to turn off anonymous telemetry
Behind the verdict
We'd reach for StereOS when the question isn't "can we sandbox this agent?" but "can we prove it can't reach the host?" Full VMs answer that in a way namespace-based isolation can't. If your security review asks about kernel separation, secure boot, or FIPS, the mb workflow is a credible answer today. The second trigger is hardware. GPU passthrough for local models via ollama or vLLM, plus bare-metal deployment rather than KVM only, puts stereOS in a different bracket from container sandboxes. Teams self-hosting inference on their own boxes will notice that gap quickly. Where it bites: the entire interface is the masterblaster CLI and jcard.toml. There's no GUI or web console, so anyone expecting a dashboard is going to bounce. The tooling is young and terminal-first, which means your team needs to be comfortable with VM concepts before mb up means anything to them. Compare it to Docker plus gVisor and you're trading convenience for separation — heavier per agent, more moving parts, but a stronger boundary. Compare it to microVM stacks like Firecracker and the pitch is that stripped virtual hardware costs you secure boot, FIPS, GPU passthrough, and working nested virtualization. If you don't need any of those, the lighter option wins on operational simplicity. In practice, run mb serve in its own terminal and treat it as infrastructure. Pull a Mixtape, write the jcard, boot, ssh in, and destroy when done — the disposal is the point. Anonymous telemetry is on by default; add the global --disable-telemetry flag if that matters to your compliance posture. Pass on this if you only need light isolation, want a managed platform, or have no appetite for Linux and VM administration. The overhead is real, and it only pays off when the isolation requirement is genuine
Limitations
- StereOS is driven entirely through the masterblaster (mb) CLI and jcard.toml configuration files, so there is no GUI or web console for the workflow.
- Install, daemon management (mb serve), sandbox lifecycle, and inspection are all command-line steps.
- Sandboxes are full VMs rather than containers or microVMs, which the docs position as heavier but more isolated (own kernel, RAM, disk, network per agent).
as of 2026-10-07
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Is StereOS still active?
StereOS is live · free · last verified 8 Nov 2026 · viability monitor.
Viability score
How well maintained and how widely used is StereOS? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about StereOS?
What people actually say about StereOS — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
Researched27 mentions across 5 sources (Hacker News, App Store, Bluesky, GitHub, Lemmy), 56 more we could not attribute · researched Nov 8, 2026.
Weighted by the 83 posts each of 5 sources contributed.
- +Full-VM isolation gives each agent its own kernel, RAM, disk, and network
- +Buys secure boot, FIPS, and GPU passthrough that container and microVM stacks lack
- +Workflow is a tight CLI loop: mb pull, mb up, mb ssh, mb down, mb destroy
- +jcard.toml makes the agent, mixtape, and prompt declarative and reproducible
- +Nested virtualization supports Kubernetes, docker compose, or agents inside the sandbox
- −Very little independent review data outside GitHub issues
- −Heavier resource footprint per agent than containers or microVMs
- −Top-level docs miss details that live only in subproject READMEs
- −Terminal-only workflow with no GUI, web console, or visual management
- −Pre-built mixtape images have shown platform-specific corruption on arm64
- • Hardware cost of full VMs — RAM and disk per agent are higher than containers
- • Engineering time to read subproject docs and build custom mixtapes
- • Time to validate on your own platform since third-party testing is scarce
How we verified this
Every listed fact about StereOS — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 8 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified StereOS 13 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed limitations, our verdict, pricing tiers, features, description, who it suits, who should skip it
- — changed who should skip it, pricing tiers, summary, our verdict, features, description, pricing page
- — changed SSL certificate
- — changed link health
- — changed our verdict, who should skip it, hidden costs, setup time, limitations, description, pricing fit, switching in, switching out, summary, features
- — changed pricing page, features, our verdict, summary, who it suits, description, pricing tiers, who should skip it, pricing model
Showing the 6 most recent of 13 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does StereOS cost in 2026?
StereOS: Free to use. Pricing last verified 8 Nov 2026.
Plans compared
Every published StereOS tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open Source (Community) | Free | — | Security-conscious developers, platform engineers, and self-hosted enterprise teams who have their own Linux host (ideally bare metal with a GPU) and are comfortable in a terminal.Adds: Starting tier — Apache 2.0 and free, with the full mb CLI, Mixtape VM images, GPU passthrough via ollama or vLLM, bare-metal support, and nested virtualization. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where StereOS's pricing actually pencils out — and where peers do it cheaper.
StereOS is Apache 2.0 and free to run, so the real cost is the hardware and operator time it consumes. Budget for a capable Linux host — ideally bare metal with a GPU if you want local-model passthrough — plus the engineering hours to learn the mb CLI and jcard.toml. That makes it cheaper on paper than commercial agent sandbox platforms that charge per seat or per agent-hour, but it's a bring-your-own-hardware proposition rather than a turnkey hosted service.
Has StereOS' pricing changed?
No plan price for StereOS has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick StereOS?
Pick StereOS if you are Security teams that need kernel-level isolation for AI coding agents, not container namespaces, Self-hosted enterprise deployments running on bare metal, Developers running local models on GPUs via ollama or vLLM inside a sandbox, Platform engineers who need agents to run Kubernetes or docker compose inside their own VM.
Look elsewhere if you are Anyone who wants a GUI or web console — the whole workflow is the mb CLI, Beginners unfamiliar with Linux, terminals, or VM concepts, Teams that only need light isolation and would be happier with Docker plus gVisor, Groups without appetite for self-hosting and VM administration.
Skip it if Skip StereOS if you want a GUI or web console, are uncomfortable living in a terminal with jcard.toml files, or only need light isolation that Docker plus gVisor already covers.
GeneratedReal-world workflow fit
Concrete scenarios for the personas StereOS actually fits — and what changes day-one when you adopt it.
Installs mb via the curl one-liner, runs mb serve, pulls opencode-mixtape with mb pull, writes a jcard.toml pointing an OpenCode harness at a prompt, then boots and connects with mb up and mb ssh to let the agent work inside a kernel-isolated VM.
Outcome: The agent can read and modify code without any host-level access, and the whole sandbox is torn down cleanly with mb down and mb destroy afterward.
Deploys stereOS on bare metal with a GPU, configures GPU passthrough, and runs ollama or vLLM inside the VM to serve an agent's model requests, using the jcard.toml to select harness and prompt.
Outcome: Model inference stays private and air-gapped inside the sandbox, with FIPS and secure boot available at the VM layer and no external platform dependency.
Boots a stereOS VM, then runs Kubernetes or Docker Compose inside it to orchestrate several agents and containers, using mb status and mb list to check on running sandboxes.
Outcome: Multi-agent orchestration is reproducible inside a single VM boundary, and the entire environment is disposable once testing wraps.
Use cases
- Sandbox a coding agent to explore untrusted codebases safely
- Run local LLM agents with GPU passthrough for private inferencing
- Deploy disposable agent environments in CI/CD pipelines
- Self-host agent infrastructure without cloud dependencies
- Experiment with multi-agent systems inside isolated VMs
- Test agent behavior in a clean, reproducible environment
Setup time & first value
How long it actually takes to get something useful out of StereOS — broken out by persona, not the marketing-page minute.
For a Linux-fluent developer with a working VM host, first value is roughly 15–30 minutes: install mb via the curl one-liner, start mb serve, pull a mixtape, write or mb init a jcard.toml, then mb up and mb ssh. Getting GPU passthrough, secure boot, or FIPS configured correctly can take substantially longer — hours, sometimes a day — depending on your hardware and platform team. Beginners
Switching to or from StereOS
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Docker plus gVisor: rebuild your agent's environment as a Mixtape, move prompts into jcard.toml, and swap container namespaces for full VM isolation
- →From Firecracker or Cloud Hypervisor: recreate the microVM workload as a stereOS full VM to regain secure boot, FIPS, GPU passthrough, and nested virtualization
- →From bare CI runners with agent scripts: replace inline agent invocation with mb up / mb ssh around a jcard-defined sandbox
- →From a host-installed coding agent: move the agent into a mixtape so it never touches the host filesystem or network directly
- ↗To Docker plus gVisor: package the agent environment as a container image and accept namespace-level rather than kernel-level isolation if you need lighter overhead
- ↗To a hosted agent sandbox platform: if you'd rather not operate bare metal, port the jcard-defined agents to a managed service and drop the CLI lifecycle
- ↗To a plain VM + Ansible workflow: bring up the same isolation with general-purpose VM tooling if you don't need mixtapes or the mb CLI
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “StereOS”, and we withheld 6: 6 could not be judged, because “StereOS” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about StereOS.
Official links
What are the best StereOS alternatives?
The closest alternatives to StereOS we list are E2B, Helix and Agentbox Sdk. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| E2B | Freemium | Pricing not published | — |
| Helix | Paid | Pricing not published | — |
| Agentbox Sdk | Freemium | Pricing not published | — |
Alternatives to StereOS
View all
E2B
E2B runs AI-generated code in isolated Linux cloud sandboxes your agents create, pause, and control on demand
Helix
Helix gives each AI coding agent its own isolated Linux desktop, a dedicated git branch, and a human approval gate before any pull request
Agentbox Sdk
Run AI coding agents in isolated cloud sandboxes — locally on your Mac or delegated from Slack, Linear, and GitHub.
Tools that pair well with StereOS
Common stack mates teams adopt alongside StereOS, with the specific reason each pairing earns its keep.
E2B
E2B runs AI-generated code in isolated Linux cloud sandboxes your agents create, pause, and control on demand
Helix
Helix gives each AI coding agent its own isolated Linux desktop, a dedicated git branch, and a human approval gate before any pull request
Agentbox Sdk
Run AI coding agents in isolated cloud sandboxes — locally on your Mac or delegated from Slack, Linear, and GitHub.
StereOS vs its closest rival
StereOS's closest head-to-head is with Spider Cloud.
Our StereOS vs Spider Cloud verdict written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Frequently asked questions
Best-of guides
For makers of StereOS
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