Inference APIs / Baseten Model Serving / Deployments alternative

Baseten alternatives for portable persistent agent work

Baseten serves models through dedicated deployments and token-priced Model APIs, with separate training workflows. Its data distribution and runtime caches help model replicas reuse selected artifacts. A durable Linux agent that calls those model services has a different filesystem and lifecycle requirement.

Reviewed 2026-10-19 · Published by the Sandbox0 team

When Baseten Model Serving / Deployments fits

Choose Baseten for managed inference, accelerator-backed model deployments, autoscaling and optimized Model APIs. Keep GPU/model serving on infrastructure suited to the model, while verifying its exact performance and availability requirements.

When to consider Sandbox0

Consider Sandbox0 for compatible Linux agents needing a durable whole writable RootFS that grows online and supports paused-file operations. The agent can use external model services while retaining tools and task state in its own runtime.

Capabilities

Baseten Model Serving / Deployments and Sandbox0: what persists?

Feature comparison with documentation and verification status
Environment and runtime lifetimeBaseten Model Serving / DeploymentsNot established in this reviewSandbox0ttl and hard_ttl default to 0 (disabled). Configure idle pause and deletion policies for the same persistent sandbox identity; an idle running sandbox still accrues compute charges.Read documentation →
Persistent filesBaseten Model Serving / DeploymentsPrivate-preview BDN volumes retain versioned read-only data; b10cache separately has cache semantics, not database durability.View evidence ↗Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFSBaseten Model Serving / DeploymentsSelected immutable data volumes and runtime cache files do not establish whole mutable replica-OS persistence.View evidence ↗Sandbox0Persistence extends beyond /workspace to paths such as /usr/local, /etc, and /home. Runtime tmpfs and virtual filesystems are excluded.Read documentation →
Release compute, keep stateBaseten Model Serving / DeploymentsScale-to-zero/recreation does not establish a returning-agent memory-preserving pause/resume contract.View evidence ↗Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process stateBaseten Model Serving / DeploymentsData distribution/caching does not establish arbitrary live-process/RAM checkpoint recovery.View evidence ↗Sandbox0Experimental memory checkpoints can preserve compatible process state. Use memory: true on both pause and resume on a compatible deployment. A filesystem checkpoint alone does not preserve running processes.Read documentation →

Online RootFS growth

On growth-enabled images, Sandbox0 automatically expands the writable RootFS as free space runs low, within a configured sparse logical ceiling up to 64 TiB. Agent processes keep running. Growth is enabled in the qualified Cloud region; confirm activation for other regions. Existing images and snapshots retain their captured storage geometry. The ceiling is logical capacity, not preallocated host disk.

Baseten distributes immutable model/data volumes and selected runtime cache artifacts across replicas. That differs from retaining and automatically growing every mutable path of one returning agent’s whole Linux RootFS.

Files while compute is paused

Sandbox0's Files API reads persistent files without resuming compute. Filesystem-only pauses also permit edits; retained-memory pauses are read-only and reject mutations with 409. SSH, SFTP, file watching, and runtime-only mounts require running compute.

BDN volume publishing/download and cache interfaces address selected model/data artifacts. They are not a native file API spanning arbitrary system paths of a paused mutable agent computer.

See paused file operations →

Volumes and runtime caches serve different state

Private-preview BDN volumes publish immutable versions mounted read-only into deployments. Runtime b10cache shares selected runtime-written files, but its guide explicitly treats it as a cache with a fallback path. Neither feature alone establishes retention of every mutable OS path across replica replacement.

Cold starts and warm replicas have billable phases

The billing guide meters production workloads, including image builds, from when the workload starts. Model loading and idle warm replicas are billable; scheduling/image pulls before start are not. Scaling replicas to zero avoids idle GPU charges, while the next request needs initialization again.

Model tokens and deployment minutes are different meters

Model APIs price input/cached-input/output tokens by model. Dedicated deployments list instance rates per minute, including separate full H100 and H100 MIG profiles. Choose the service and actual instance before estimating cost; a token price is not a generic machine rental.

Pricing

Compare billing models, then price your workload

CPU allocation, memory, billing minimums, disk, plan fees, and supported workload differ. These meters are not equal-performance machine quotes. Confirm region, resource units, and included allowances before estimating a total.

Baseten Model Serving / Deployments

Pricing reviewed 2026-10-19

Basic platform fee
$0/month + usage
Dedicated deployments, Model APIs and training have their own meters.
Rate source ↗
Dedicated H100 80 GiB VRAM reference
$0.10833 per instance-minute
Published Minute view; full H100 profile differs from MIG.
Rate source ↗
Dedicated H100 MIG 40 GiB reference
$0.0625 per instance-minute
Different accelerator profile; do not infer equal model capacity.
Rate source ↗
Dedicated CPU 2x8 reference
$0.00173 per instance-minute
2 vCPU / 8 GiB RAM profile; confirm current deployment scope/region.
Rate source ↗

Use the selected instance and billable lifecycle, including applicable build, loading and warm-replica time. Model API token charges, training and enterprise/self-host deployments have different terms. Private-preview volumes require access; caches need a miss/rebuild path.

Check current Baseten Model Serving / Deployments pricing ↗

Sandbox0

$0.015/GiB-hour compute (billed by the second at approximately $0.000004167/GiB-second), plus $0.02/GiB-month of retained incremental RootFS and memory checkpoint data. Shared base images and platform recovery retention are excluded; paused sandboxes accrue storage charges only.

Compute / GiB-hour
$0.015
Retained data / GiB-month
$0.02
Paused compute
$0.00

A 4 GiB agent, 100 running hours

$6.00 compute

4 GiB × 100 hours, billed by the second. Keeping 20 GiB of billable incremental data for a full billing month adds $0.40. CPU is derived from memory by the platform; choose a tier that fits your workload.

Understand storage billing →

Before migrating from Baseten Model Serving / Deployments

  1. Separate Model APIs, dedicated deployments and training; inventory instance profiles, billable phases, BDN volumes and cache dependencies.
  2. Keep required model/GPU serving and move compatible Linux agent orchestration and durable files to the appropriate runtime.
  3. Test model/result handoff, system retention, growth, paused files and complete model/deployment, storage and Linux runtime costs.

Common questions

Is Sandbox0 a drop-in Baseten Model Serving / Deployments replacement?

Evaluate API compatibility and product scope. These products serve different core workflows, so a change may require a different architecture.

Does keeping files also keep a running agent?

Filesystem state and volatile process state are separate. Sandbox0 requires explicit compatible memory checkpoints to preserve running processes; its default filesystem resume starts fresh processes.

Sources and review scope

The Boat team's Battleships directory is the discovery source. References below describe the product and plan discussed on this page. Check current availability, regional terms and billing units before migrating. Where the cited material does not establish a capability or price, the comparison identifies that uncertainty.

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