Code execution sandboxes have become essential infrastructure for AI-powered development workflows. As coding agents, AI assistants, and automated development tools generate and execute code autonomously, secure isolation is no longer optional; it's foundational. Windsurf, the agentic IDE that Cognition acquired in July 2025, now ships under the name Devin Desktop. Windsurf developers and teams building AI-native applications need sandbox environments that run securely across large numbers of parallel sessions, get the CPU and memory each task needs without overprovisioning, and start consistently as usage grows. This guide examines seven code execution sandbox platforms serving different development needs in 2026, starting with Modal's secure sandboxes. Modal is a scalable, high-performance sandbox platform for executing AI-generated code at production scale, with optional GPU access for workloads that require acceleration.
Key Takeaways
1. Modal
Modal is a scalable, high-performance sandbox platform for executing AI-generated code at production scale, with on-demand GPU access available when workloads require acceleration. Its sandboxes combine high concurrency, automatic CPU and memory bursting, and consistent fast starts under load. Modal provides code-first SDKs in Python, TypeScript, and Go. Sandboxes support all programming languages; the SDK language used to define and manage sandboxes is independent of what runs inside them.
Core Capabilities
Security and Compliance
Modal has successfully completed a SOC 2 Type II audit; Modal's January 2025 announcement stated that no deviations were found in that audit. Modal supports HIPAA-compliant workloads on Enterprise plans via a BAA. Security infrastructure includes TLS 1.3 for public APIs, encryption for data in transit and at rest, and compute isolation through VM and gVisor sandboxes. Modal supports region-pinning.
Production-Proven Results
Modal powers cloud infrastructure for over 10,000 teams, including AI companies building production applications:
Why Teams Choose Modal for Windsurf
2. E2B
E2B provides sandboxes for AI agents, focusing on ephemeral code execution with Firecracker microVM isolation.
Capabilities
Considerations
Why Teams Choose E2B
E2B is a sandbox-only vendor with an open-source core and bring-your-own-cloud deployment, and it has run 1 billion sandboxes in total. Teams choose E2B when they want a separate sandbox point solution for running the code their Windsurf agents produce.
3. Northflank
Northflank provides a full-stack cloud platform with sandbox capabilities, and each sandbox runs in its own microVM on Cloud Hypervisor. The platform offers self-serve BYOC deployment.
Capabilities
Considerations
Why Teams Choose Northflank
Northflank is a full-stack cloud platform that treats sandboxes as one service among several. Teams choose Northflank when data residency rules or existing cloud contracts mean their Windsurf agents' sandboxes have to live in their own cloud account beside their other workloads.
4. Daytona
Daytona provides isolated sandboxes and development environments built with a focus on persistence, offered as a managed cloud service.
Capabilities
Considerations
Why Teams Choose Daytona
Daytona is a single-purpose sandbox provider where persistence is the default and starts are quick at smaller volumes. Teams choose it as a point solution for stateful coding agents tied to a Windsurf project when they don't need high concurrency.
5. Koyeb
Koyeb offers a serverless sandbox platform currently in public preview, with scale-to-zero architecture and SDK-driven sandbox creation. Sandboxes run as part of Koyeb's broader managed deployment platform.
Capabilities
Considerations
Why Teams Choose Koyeb
Koyeb is a serverless deployment platform that offers sandboxes next to its application hosting. Teams choose Koyeb when they want short-lived sandboxes for Windsurf-generated code on the same managed platform where they already deploy their services.
6. Fly.io Sprites
Fly.io Sprites provides persistent VM-based sandboxes with checkpoint and restore capabilities. The platform focuses on maintaining state across sandbox sessions in hardware-isolated VMs.
Capabilities
Considerations
Why Teams Choose Fly.io Sprites
Fly.io Sprites is a persistent-machine offering inside the Fly.io cloud, built around checkpoints and restores. Teams choose Sprites when each Windsurf agent should keep one long-lived machine whose disk survives between occasional sessions.
7. Vercel Sandbox
Vercel Sandbox provides isolated code execution environments in Linux microVMs. The platform uses Firecracker for isolation and is part of the broader Vercel platform.
Capabilities
Considerations
Why Teams Choose Vercel
Vercel Sandbox is a component of Vercel's cloud platform. Teams choose it when the apps their Windsurf agents build already deploy on Vercel and they want CPU billed on active time, accepting memory billed as provisioned.
Why Modal Stands Out for Windsurf Development
Proven Scale for Production Workloads
Modal supports up to 1M concurrent sandbox sessions and has demonstrated creating 1M+ sandboxes in under a minute. Tens of thousands of concurrent customer sandboxes run on Modal on a regular basis, and Modal reports running 3 billion sandboxes as of October 2026. Quora runs millions of daily executions of untrusted code on Modal, and Imbue orchestrates hundreds of isolated coding agents on the platform. For teams building multi-tenant SaaS products or high-traffic AI applications, this proven scale reduces operational risk.
CPU and Memory Bursting
Windsurf workloads rarely use resources evenly. An agent can sit idle while it waits on a model response or a developer's review, then need full CPU and memory to install dependencies, compile a project, or run a test suite. Fixed-reservation pricing forces teams to size every sandbox for that heaviest step, so most of the capacity they pay for goes unused. On Modal, each sandbox requests a modest amount of CPU and memory and goes past that request automatically when a Windsurf task calls for it, which lets teams provision for typical usage instead of peak usage. Modal bills per second on whichever is greater, requested or actual resources, and the extra headroom also reduces the risk of out-of-memory failures.
Consistent Startup Under Load
Modal's custom-built scheduler and optimized filesystem keep sandbox starts sub-second and consistent as concurrency rises, including with large custom images. Memory Snapshots can further reduce initialization-heavy cold starts by restoring initialized state rather than starting from scratch. For interactive AI applications where response time matters, this performance engineering translates to better user experience.
Code-First SDKs
Modal provides code-first SDKs in Python, TypeScript, and Go, with sandboxes supporting all programming languages. Teams define container images, compute requirements, and scaling behavior directly in application code.
GPU Sandboxes When Agents Need Them
Most Windsurf agent workflows run on CPU, but some need acceleration for ML inference or model-based code analysis. Modal's GPU sandboxes keep full sandbox functionality across a broad GPU lineup of 10+ types, including B300, B200, H200, H100, A100, L40S, L4, A10, T4, and RTX Pro 6000 Blackwell, without reservations. For Windsurf developers building AI-native applications, this means coding agents can securely execute generated code and run ML inference within the same infrastructure.
Unified AI Infrastructure Platform
Beyond sandboxes, Modal provides a complete AI infrastructure platform including inference serving, model training, and batch processing. This unified approach eliminates the need to manage multiple vendors and separate billing relationships. For Windsurf developers building AI applications that span code execution, ML inference, and compute-intensive workloads, Modal consolidates infrastructure complexity.
Enterprise Security Without Compromise
Modal has successfully completed a SOC 2 Type II audit; Modal's January 2025 announcement stated that no deviations were found in that audit. Modal supports HIPAA-compliant workloads on Enterprise plans via a BAA. The combination of VM and gVisor isolation, TLS 1.3, encryption for data at rest and in transit, and region-pinning meets the security bar that regulated industries require.
Get started with Modal'ssandbox documentationto build secure, scalable code execution for your Windsurf applications.
Frequently Asked Questions
A code execution sandbox is an isolated environment where code runs separately from the host system and other workloads. For AI development, sandboxes are critical because AI agents and coding assistants generate code autonomously, without human review before execution. Sandboxes prevent malicious or buggy generated code from accessing unauthorized resources, affecting other workloads, or causing system damage. Modal uses VM and gVisor sandboxing for compute isolation, while platforms like E2B and Vercel use Firecracker microVMs.
Modal has successfully completed a SOC 2 Type II audit; Modal's January 2025 announcement stated that no deviations were found in that audit. For healthcare and regulated industries, Modal supports HIPAA-compliant workloads on Enterprise plans via a BAA. The security infrastructure includes VM and gVisor isolation, TLS 1.3 for public API connections, and encryption for data both in transit and at rest. Modal supports region-pinning and also publishes vulnerability remediation SLAs with target timeframes for addressing security issues.
Yes. Modal's platform includes dedicated inference and training products, so teams can pair secure code execution with Modal-hosted model serving or fine-tuning without adding another vendor. Sandboxes can also call upon GPUs when workloads require acceleration, with 10+ types including B300, B200, H200, H100, A100, L40S, L4, A10, T4, and RTX Pro 6000 Blackwell. This enables AI agents to execute generated code securely and run ML inference or fine-tuning within the same infrastructure.
Modal's dedicated inference and training products sit on the same platform as its sandboxes, so GPU-backed model work and sandboxed code execution share one set of infrastructure. Teams don't need to provision or manage clusters, and GPU sandboxes are available without reservations. For CPU and memory, sandboxes start from a requested baseline and burst above it automatically, with billing per second on the greater of requested and actual resources. Modal's custom-built scheduler keeps sandbox starts sub-second and consistent even at high concurrency.
Modal offers a Starter plan that includes compute credits each month, allowing teams to experiment with sandboxes and other platform capabilities before committing to higher tiers. Usage beyond the included credits is billed per second on the greater of requested and actual resources. See the Modal documentation to get started with sandbox development.
Modal's fast scheduling and optimized filesystem reduce startup latency. Memory Snapshots can reduce initialization-heavy startup work by restoring initialized CPU or, in alpha, GPU memory state. For GPU workloads, Memory Snapshots are most useful for skipping initialization work such as CUDA and library setup or JIT compilation.
Modal bills for active resources. A sandbox requests a CPU and memory size, can exceed that size automatically when a Windsurf task needs more, and is charged per second for whichever is larger: the requested resources or the resources actually used. That lets teams size sandboxes for the routine work of editing files and waiting on the model, while still covering a full build or test run at peak with a lower chance of out-of-memory failures. Most Sandbox providers bill for a fixed reservation that a sandbox cannot exceed, so teams reserve enough for their largest Windsurf task and pay for capacity that stays idle through most of each session.
