Cursor Agent and similar AI coding assistants generate unprecedented volumes of code that needs to run somewhere safe. When your agent produces code autonomously, executing it on your local machine or shared infrastructure creates security risks that can cascade into production incidents. The solution is a code execution sandbox, an isolated environment purpose-built for running AI-generated code securely at scale. Choosing the right sandbox environment determines whether your Cursor Agent can execute code safely, scale without manual intervention, and access GPU acceleration when workloads demand it.
This guide examines seven code execution sandboxes serving different Cursor Agent needs in 2026, starting with Modal, a serverless compute platform built for secure code execution at massive concurrency with on-demand GPU support layered on top.
Key Takeaways
- Secure isolation protects against untrusted code execution: Cursor Agent generates code autonomously, making sandboxed execution critical. Modal uses gVisor containers for compute isolation, while E2B employs Firecracker microVMs, and both approaches prevent AI-generated code from affecting other workloads
- Cold start performance varies across platforms: Several platforms, including Blaxel and Daytona, support sandbox startup; Modal delivers fast startup through an optimized filesystem and snapshotting techniques, with performance differences compounding when provisioning thousands of sandboxes
- GPU support differentiates platforms for ML workloads: Modal combines secure sandboxing with native GPU access, including H100, A100, L4, and more, enabling Cursor Agent to run ML inference and training alongside code execution without leaving the platform
- Session limits impact long-running agent workflows: Some platforms cap sessions at 24 hours while others offer unlimited runtime, a critical consideration for agents maintaining state across extended workflows
- Production-proven platforms reduce operational risk: Modal powers infrastructure for over 10,000 teams, demonstrating enterprise-scale reliability for agent workloads
1. Modal
Modal delivers serverless compute for secure code execution at scale, the core sandbox workload for Cursor Agent, with on-demand GPU access layered on top for workloads requiring acceleration. The platform takes your code, containerizes it, and executes it in the cloud with automatic scaling, all defined through a code-first SDK with support for Python, TypeScript, and Go.
Core Capabilities
- gVisor container isolation: Secure sandboxed execution for running AI-generated code, the primary workload for coding agent sandboxes
- Massive concurrent scale: Supports 50,000+ concurrent sessions, enabling Cursor Agent to spin up thousands of parallel execution environments
- Fast cold starts: Engineered for fast cold starts and faster feedback loops, with an optimized filesystem that helps containers come online quickly without letting large images slow startup down
- Native GPU support: Agents can call upon GPUs when workloads require acceleration (Sandbox GPU example), with options including T4, L4, A10, L40S, A100 (40GB and 80GB), RTX PRO 6000, H100, H200, and B200/B200+, enabling ML inference alongside code execution
Security and Compliance
Modal maintains SOC 2 Type II certification and supports HIPAA-compliant workloads on Enterprise plans via a BAA. Modal Sandboxes are built on gVisor, which provides strong isolation properties and custom logic to prevent malicious system calls; Sandboxes are not authorized to access other Modal workspace resources by default. The platform uses TLS 1.3 for public APIs, and user data is encrypted in transit and at rest.
Production-Proven Results
Modal powers production workloads for notable AI companies:
- Lovable used Modal to run over 1 million sandboxes during a 48-hour event, peaking at 20,000 concurrent sandboxes
- Quora uses Modal Sandboxes to execute LLM-generated code in Poe and stress-tested Sandbox creation throughput to 1,000 Sandboxes per second
- Ramp uses Modal Sandboxes for background coding agents that generate code changes and write them back into commits or pull requests
- The platform's code-first approach, with SDKs in Python, TypeScript, and Go, eliminates YAML configuration, enabling faster iteration cycles
- Modal's serverless pricing means teams pay for actual compute usage rather than idle resources; Modal Functions scale to zero by default when there are no inputs, and Modal Sandbox pricing is usage-based
What Makes Modal Unique
- AI-native container runtime: Custom-built infrastructure including file system, container runtime, scheduler, and image builder optimized for AI workloads
- GPU + sandboxing combination: Modal combines native GPU support with secure sandboxed execution, enabling Cursor Agent workflows that need ML inference alongside code execution without leaving the platform
- Code-first SDK: Define compute, storage, and networking via code in Python, TypeScript, or Go, eliminating configuration overhead
Best For: Teams using Cursor Agent that need secure code execution at scale, with on-demand GPU access when workloads require ML inference, model fine-tuning, or compute-intensive analysis.
2. E2B
E2B specializes in secure sandboxes for AI agents, focusing on ephemeral code execution with Firecracker microVM isolation. The platform reports being used by 88% of Fortune 100 companies and has processed over 500 million started sandboxes.
Core Capabilities
- Firecracker microVMs: Hardware-level isolation using the same technology that powers AWS Lambda, providing kernel-level separation for untrusted code
- Supports cold starts: E2B supports sandbox startup in the same region, with quick start times available across regions
- Multi-language SDKs: Support for Python and TypeScript with integrations for LangChain, OpenAI, and Anthropic
- Open-source option: Self-hosting available for organizations with data sovereignty requirements
Customer Validation
E2B has notable enterprise traction:
- Perplexity shipped advanced data analysis in one week using E2B sandboxes
- Hugging Face used E2B to scale out training runs for Open R1, launching hundreds of sandboxes in experiments
- The platform reports 2 million+ monthly downloads across NPM and PyPI
Use Case Focus
E2B excels at ephemeral code execution, spinning up isolated environments for agents to run generated code, then tearing them down. Session limits cap at 24 hours on Pro plans and 1 hour on free tiers.
Best For: Teams building Cursor Agent integrations focused on code execution and testing where GPU acceleration is not required, particularly those needing sandbox cold starts and mature SDK ecosystem.
3. Daytona
Daytona provides persistent development environments with sandbox spin-up, making it a strong performer in the category. The platform's open-source approach and enterprise validation from companies like LangChain make it a solid contender for high-scale workloads.
Core Capabilities
- Sandbox spin-up: Sandbox environments spin up quickly, well-suited for high-throughput evaluation pipelines
- Persistent environments with configurable lifecycle: Daytona supports persistent environments and configurable lifecycle behavior; stopped sandboxes preserve filesystem state, with auto-stop, auto-archive, and auto-delete options available
- Multi-language SDKs: Support for Python, TypeScript, Ruby, and Go
- Full dev environment features: Git integration, LSP support, and Docker-in-Docker capabilities
Customer Validation
Daytona has earned endorsements from prominent AI infrastructure companies:
- Harrison Chase, CEO of LangChain: "Daytona jumped in, contributed a working PR within hours, and fully unblocked us"
- SambaNova: "When you're provisioning tens of thousands of sandboxes, those milliseconds add up"
- Additional customers include Prosus
Architecture Approach
Daytona focuses on persistent workspaces that maintain state across sessions. This benefits Cursor Agent workflows that need to preserve context, cached dependencies, or intermediate results without recreation overhead. The platform offers GPU support alongside its persistent storage model.
Best For: Teams using Cursor Agent that require persistent development environments with GPU access, configurable lifecycle controls, and prefer open-source infrastructure transparency.
4. Northflank
Northflank provides a full-stack AI infrastructure platform that extends beyond sandboxes to include databases, APIs, GPU compute, and CI/CD in a unified control plane. The platform processes over 2 million isolated workloads monthly and offers flexible isolation technology choices.
Core Capabilities
- Configurable isolation: Northflank uses Kata Containers with Cloud Hypervisor by default, with gVisor as an alternative when nested virtualization is unavailable
- Self-serve BYOC: Bring Your Own Cloud deployment across AWS, GCP, Azure, Oracle, CoreWeave, and bare-metal infrastructure
- Long-running workloads: Northflank supports long-running agents, persistent and ephemeral workloads, and thousands of concurrent sessions
- Full-stack platform: Sandboxes plus databases, APIs, GPU compute, and CI/CD in one control plane
Customer Validation
Northflank powers production infrastructure for established companies:
- David Cramer, Co-Founder of Sentry: "Northflank is way easier than gluing a bunch of tools together to spin up apps and databases"
- The platform has processed 130 billion+ requests
- Additional customers include Writer and Weights
Enterprise Features
Northflank maintains SOC 2 Type 2 certification and offers GPU support including H100 and A100. The BYOC model gives organizations more control over infrastructure placement, compliance boundaries, and cloud-provider economics; actual cost savings depend on workload and contract terms.
Best For: Enterprise teams needing production-grade infrastructure beyond sandboxes, with BYOC deployment options and compliance requirements.
5. Blaxel
Blaxel is a sandbox platform built specifically for AI agents, with a focus on persistent "agent computers" that stay on standby and resume quickly when needed. The platform is designed around resume times from standby.
Core Capabilities
- Resume: Sandboxes resume from standby quickly, well-suited for interactive coding assistants
- Standby mode at zero compute cost: Blaxel says sandboxes can remain on standby at zero compute cost; check the Blaxel website for current storage billing terms during standby
- MicroVM isolation: Hardware-enforced kernel separation using the same technology as AWS Lambda
- Co-located agent hosting: Eliminates network latency between agent and sandbox
Compliance and Security
Blaxel maintains comprehensive compliance certifications including ISO 27001, SOC 2 Type II, and HIPAA BAA availability. The platform positions itself around secure sandboxed compute runtimes with file system and process access exposed through REST API and MCP server.
Architecture Approach
Blaxel emphasizes persistent state rather than purely ephemeral execution. The platform's documentation recommends treating sandboxes as persistent computers that retain shell history, installed dependencies, and context over time, beneficial for Cursor Agent workflows requiring continuity across sessions.
Best For: Teams building Cursor Agent integrations that need persistent sandbox environments, sandbox resume times, and latency-sensitive agent applications.
6. Fly.io Sprites
Fly.io Sprites provides persistent Firecracker microVMs with a 100 GB starting partition that can scale as needed. The platform's idle billing model and checkpoint/restore capabilities make it cost-effective for sporadic usage patterns.
Core Capabilities
- Persistent storage: Sandboxes start with a 100 GB partition backed by object-storage persistence and local NVMe caching, enabling full project persistence across sessions
- Idle billing model: Stop paying when sandbox is inactive, but state persists
- Checkpoint/restore: Resume from saved state quickly
- Firecracker isolation: Hardware-level microVM isolation with ext4 filesystem
Customer Base
Fly.io serves companies including Builder.io, Mercor, Imbue, and Supabase. The platform is a strong option for agents that maintain long-running projects across multiple sessions.
Use Case Focus
Fly.io Sprites excels at persistent state workflows, with cold activation and checkpoint restore capabilities. The idle billing model and persistent storage make it well-suited for Cursor Agent workflows that need to preserve large project contexts across days or weeks.
Best For: Teams using Cursor Agent for long-running projects requiring large persistent state and workspace continuity across days or weeks.
7. CodeSandbox (Together AI)
CodeSandbox, acquired by Together AI in December 2024, provides snapshot-based microVM sandboxes with browser IDE capabilities. The platform combines secure code execution with collaborative development features.
Core Capabilities
- Firecracker microVMs: Secure isolation with snapshot-based hibernation
- VM restore: CodeSandbox says its SDK can spin up, clone, or restore microVM sandboxes quickly, with sandbox resume and clone operations supported
- Template ecosystem: Pre-configured environments for web frameworks and common development setups
- Browser-based IDE: Collaborative development capabilities alongside API access
Compliance and Architecture
CodeSandbox maintains SOC 2 Type II certification. The platform supports hibernation and configurable lifecycle behavior for persisting sandboxes across sessions. The Together AI acquisition connects CodeSandbox to Together AI's broader AI infrastructure strategy, but no public CodeSandbox GPU integration roadmap has been confirmed.
Use Case Focus
CodeSandbox is geared toward web-focused agent workflows with browser-based collaboration. The snapshot and forking architecture enables parallel agent runs and quick environment duplication.
Best For: Teams building Cursor Agent integrations focused on web development workflows, needing browser-based collaboration and template-based environment configuration.
Why Modal Sandboxes Stand Out for Cursor Agent
Purpose-Built for Agent Workloads
Modal's architecture is specifically engineered for agentic and machine learning workloads. The platform's custom container runtime, scheduler, and file system are optimized for the unique demands of elastic infrastructure with fast cold starts, sandboxed code execution, GPU-accelerated computation, and dynamic scaling that Cursor Agent workflows require.
Secure Sandboxed Execution at Scale
Most Cursor Agent sandbox work is CPU-based execution of generated code, and Modal's sandboxes are built to handle that workload at scale. The platform supports 50,000+ concurrent sessions with fast startup, gVisor isolation, and full observability, essential for coding agents that generate and execute untrusted code.
GPU + Sandbox Combination
On top of the CPU baseline, agents can call upon GPUs on demand when workloads require acceleration, with native GPU support alongside sandboxed execution available in the platform. Modal supports a full GPU lineup including T4, L4, A10, L40S, A100 (40GB and 80GB), RTX PRO 6000, H100, H200, and B200/B200+, letting Cursor Agent match compute to the task at hand, whether running code analysis models or large language models for generation.
Code-First Developer Experience
The code-first SDK, available in Python, TypeScript, and Go, eliminates infrastructure configuration overhead. Teams define compute requirements, container images, and scaling behavior directly in code using decorators. This approach enables rapid iteration that YAML-based platforms struggle to match.
Production-Proven Enterprise Scale
Modal powers cloud infrastructure for over 10,000 teams, including AI companies running production workloads at scale. This track record demonstrates the platform's ability to handle enterprise-scale Cursor Agent deployments reliably.
Enterprise Security and Compliance
With SOC 2 Type II certification, HIPAA support via BAA on Enterprise plans, and comprehensive security practices including gVisor sandboxing and TLS 1.3, Modal meets the compliance requirements that enterprise Cursor Agent deployments demand.
For teams building Cursor Agent integrations that require secure code execution, production-grade reliability, and on-demand CPU and GPU access, Modal's combination of AI-native infrastructure, sandboxed execution at scale, and proven enterprise scale makes it the clear choice.
Explore the Modal documentation to get started building with Cursor Agent and secure sandboxed execution.
View Modal Docs