Modal Sandboxes vs Railway Sandboxes

Modal Sandboxes and Railway Sandboxes both run untrusted or agent-generated code in isolated environments, but they optimise for different workflows. Modal provides programmable CPU and GPU compute with outbound restrictions, inbound tokens and tunnels, and CIDR controls, while Railway focuses on branchable development workspaces connected to Railway projects.

• Modal Sandboxes use gVisor and support Python, JavaScript/TypeScript, and Go SDKs, custom images, GPUs, snapshots, Volumes, and network policies.
• Railway Sandboxes run on Railway's virtual-machine primitive and combine dashboard, CLI, TypeScript SDK, and SSH access with Docker, checkpoints, forks, private networking, and several preinstalled coding agents.
• Modal Sandboxes have a five-minute default maximum lifetime and can run for up to 24 hours. Railway Sandboxes use configurable idle timeouts of up to 120 minutes on Hobby and Pro.
• Modal bills by the second using the greater of requested or actual CPU and memory usage. Railway bills allocated CPU and memory by the minute while a Sandbox runs, including idle periods.
• Northflank adds persistent and ephemeral CPU and GPU sandboxes with no platform-imposed session-duration limit. Teams can also use self-serve BYOC and BYOK to deploy agent workloads in their own infrastructure.

Modal Sandboxes are secure containers for running untrusted user or agent code, including model-generated programs, repository tests, and temporary environments with custom dependencies.

Standard Modal Sandboxes use gVisor, which handles system calls through a user-space kernel. They cannot access other Modal workspace resources by default.

Python, JavaScript/TypeScript, and Go SDKs control the environment. The default is Debian Linux with Python, while Modal Images support package installation, Dockerfile-style operations, and registry images.

CPU and memory requests establish guaranteed resources, with bursting when spare host capacity is available. Modal also supports GPU Sandboxes. A separate Beta, CPU-only VM Sandbox runtime provides a full Linux kernel and broader Docker compatibility.

Railway Sandboxes are short-lived Linux environments for agent runners, application tests, and tasks requiring filesystem and shell access.

Each runs on Railway's virtual-machine primitive and supports dashboard, CLI, TypeScript SDK, and SSH access. Preinstalled Docker can pull images, build Dockerfiles, and run containerised dependencies.

The default image includes git, Node.js, npm, mise, and preinstalled coding agents including Claude Code, OpenAI Codex, Cursor agent, Droid, OpenCode, and Pi. Templates define repeatable setup, checkpoints preserve prepared disk state, and forks branch an existing Sandbox.

Railway Sandboxes remain in Priority Boarding, Railway's opt-in beta program, as of July 2026.

This comparison reflects product availability, capabilities, and pricing on 23 July 2026.

Northflank's column refers to sandbox workloads implemented through its broader service and compute primitives. The platform context is part of the comparison where persistence, GPUs, or customer-owned infrastructure changes the deployment decision, but it is not a one-to-one match for every Modal or Railway Sandbox API.

Standard Modal Sandboxes use gVisor, which places a user-space kernel between the workload and host kernel. Each Sandbox is created from a Modal Image with configurable CPU, memory, storage, networking, and optional GPU resources.

Railway Sandboxes run on Railway’s virtual-machine primitive. Each environment includes its own filesystem, shell, and Docker daemon, allowing agents and developers to build images and run containerised dependencies without deploying a Railway service.

Modal Sandboxes are controlled through Python, JavaScript/TypeScript, and Go SDKs. Applications can create environments, select Images, allocate resources, execute commands, transfer files, configure network access, and terminate Sandboxes programmatically.

Railway Sandboxes support dashboard, CLI, TypeScript SDK, console, and SSH workflows. The default image includes Docker and preinstalled coding agents. Teams can prepare a workspace, checkpoint its disk, and fork that state across parallel agent tasks.

Modal provides outbound blocking and allowlists, authenticated Connect Tokens, port tunnels, inbound CIDR controls, and private IPv6 between Sandboxes in the same workspace and region.

Railway Sandboxes can join their Railway environment’s private network to reach databases, Redis, internal services, and project variables. CLI port forwarding makes services inside a Sandbox accessible from localhost.

Modal supports filesystem snapshots, directory snapshots (in Beta as of July 2026), experimental memory snapshots, and mounted Volumes. Modal Sandboxes have a five-minute default maximum lifetime, configurable up to 24 hours. Memory snapshots expire after seven days and cannot be used with GPU Sandboxes.

Railway provides templates for repeatable setup, checkpoints for prepared disk state, and forks for branching active workspaces. Sandboxes use configurable idle timeouts of up to 120 minutes on Hobby and Pro.

Modal and Railway use different billing models, so their headline rates are not directly equivalent.

Modal bills Sandboxes by the second using whichever is greater: the requested resources or actual consumption. CPU costs $0.1419 per physical core-hour, with one physical core equivalent to two vCPUs. Memory costs $0.0240 per GiB-hour, while GPU Sandboxes use Modal’s standard GPU pricing.

Railway bills the CPU, memory, and network egress consumed while a Sandbox runs. Memory costs approximately $50 per GB-month, vCPU costs approximately $50 per vCPU-month, and egress costs $0.05 per GB. Idle Sandboxes continue consuming billable resources, so destroying unused environments or setting shorter idle timeouts reduces costs.

Modal Sandboxes have a maximum lifetime of 24 hours. GPU Sandboxes may be subject to preemption, and explicit region selection adds a 1.5x to 1.75x multiplier to base usage prices. Experimental memory snapshots cannot be used with GPUs and must be restored on the same instance type.

Railway Sandboxes remain in Priority Boarding as of July 2026. They use idle timeouts and running-resource billing, and no GPU option is listed.

For workloads requiring persistent GPU environments, longer-running execution, or deployment in your own infrastructure, Northflank supports persistent and ephemeral sandboxes on Northflank Cloud, BYOC, and BYOK.

Choose Modal Sandboxes when execution is embedded in an application through Python, JavaScript/TypeScript, or Go and requires configurable resources, GPUs, snapshots, Volumes, or Sandbox-specific network controls. Check that the 24-hour maximum lifetime and regional pricing fit the workload.

Choose Railway Sandboxes when agents or developers need an interactive Linux workspace with Docker, SSH, private access to Railway services, and branchable disk state. Templates, checkpoints, forks, and preinstalled coding agents make Railway useful for repository work, integration tests, and parallel agent tasks.

Northflank Sandboxes cover more than isolated command execution. Teams can run persistent or ephemeral CPU and GPU sandboxes with workload-specific microVM or gVisor isolation, attached volumes, high concurrency, and no platform-imposed session-duration limit.

The same platform runs APIs, workers, jobs, databases, object storage, preview environments, inference, and training workloads alongside the sandbox fleet. Deploy on Northflank Cloud, use self-serve BYOC in your cloud accounts, bring existing Kubernetes clusters with BYOK on-premises or on bare metal, or deploy into customer VPCs.

Northflank Skills let Claude Code, Codex, Gemini CLI, and Cursor configure sandboxes, deploy services, manage databases, operate GPU workloads, and create preview environments through the Northflank API and CLI. This gives coding agents a path from isolated execution to controlled preview, staging, and production workflows.

Modal provides programmable, resource-elastic execution, while Railway provides branchable development and agent workspaces integrated with Railway projects. Northflank combines persistent and ephemeral sandbox execution with the APIs, jobs, databases, GPUs, and deployment infrastructure needed to run agent workloads in production.

Modal Sandboxes use gVisor by default, while Railway Sandboxes run on Railway’s virtual-machine primitive. Northflank applies microVM or gVisor isolation depending on the workload and infrastructure, on Northflank Cloud or through BYOC.

Modal Sandboxes have a five-minute default maximum lifetime and can run for up to 24 hours. Railway Sandboxes use idle timeouts of up to 120 minutes on Hobby and Pro. Northflank imposes no fixed session-duration limit, and sandboxes can be paused, resumed, or scaled to zero.

Modal bills the greater of requested or actual CPU and memory consumption by the second. Railway bills CPU and memory by the minute while a Sandbox runs, including while idle, plus egress. Northflank Cloud prorates managed compute to the second and also offers BYOC for teams that want to run sandboxes on their own infrastructure.

Modal supports GPU Sandboxes that may be subject to preemption. Railway does not list a GPU configuration or allocation option for Railway Sandboxes. Northflank supports persistent and ephemeral GPU sandboxes on managed infrastructure and through self-serve BYOC.

Modal suits application-embedded agent execution that needs programmable resources and network controls. Railway suits interactive, branchable workspaces integrated with Railway services. Northflank fits production agent infrastructure that needs persistent environments, GPUs, high concurrency, BYOC, or a path from isolated execution to preview, staging, and production workflows through Northflank Skills.

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• Persistent sandboxes: Learn when agents need durable filesystems and long-running execution environments.
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• Best platforms for high-concurrency sandbox environments: Evaluate fleet scaling, orchestration, and infrastructure control for large sandbox workloads.