Mastra has emerged as a leading TypeScript AI agent framework, with 20k+ GitHub stars and over 300k weekly npm downloads reported in its 1.0 announcement. Building production-ready AI agents with Mastra requires secure sandbox environments where generated code can execute safely at scale. The right sandbox infrastructure determines whether your agents can run untrusted code securely, scale without manual intervention, and access GPU acceleration when ML workloads demand it.
This guide examines seven sandbox platforms serving different Mastra agent needs in 2026, starting with Modal, which offers serverless Sandboxes with GPU support and secure CPU-based code execution.
Key Takeaways
- GPU capability is a critical differentiator: Modal supports GPU Sandboxes with serverless autoscaling, making it a strong choice for Mastra agents running ML inference or model fine-tuning
- Mastra's official sandbox provider ecosystem is broad: E2B, Daytona, Blaxel, Modal, and Vercel offer native
@mastra/* packages, alongside local execution and AgentCore Runtime, per the current Mastra sandbox docs - Security isolation varies by architecture: Modal uses gVisor containers, E2B and Vercel employ Firecracker microVMs, and Daytona documents OCI/Docker-compatible workflows with namespace and resource isolation, each using a different isolation approach for untrusted code execution
- Cold start behavior varies by platform: Blaxel, Daytona, and E2B support cold starts, while RunPod startup depends heavily on container image and model-loading path
- Scale requirements differ by workload: Modal supports 100k+ concurrent sandboxes, while E2B lists 20 concurrent sandboxes on Hobby and 100 on Pro by default, with purchasable Pro concurrency up to 1,100 and custom Enterprise limits
1. Modal
Modal delivers serverless compute for secure code execution at scale, with native GPU support for demanding ML workloads. Mastra now documents a Modal sandbox provider via @mastra/modal, and Modal is a strong choice when your Mastra agents need GPU compute for ML inference, model fine-tuning, or compute-intensive analysis.
Core Capabilities
- gVisor container isolation: Secure sandboxed execution for running AI-generated code, supporting 100k+ concurrent sandboxes with fast cold starts
- Native GPU support: Modal offers serverless GPU access for Functions and GPU-capable Sandboxes, with a broad lineup including T4, L4, A10, L40S, A100 variants, H100, H200, and B200
- Code-first SDK: Define compute, storage, and networking in code without YAML configuration. Modal supports SDKs and code-defined infrastructure in Python, TypeScript, and Go for using Functions, running Sandboxes, and managing Modal resources. Code running inside a Sandbox is not limited to one language; a Sandbox can run whatever runtime or language the workload requires
- Scale-to-zero architecture: Automatic scaling to thousands of containers with no idle infrastructure costs
- 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
Security and Compliance
Modal maintains SOC 2 Type II certification. Modal supports HIPAA-compliant workloads on Enterprise plans via a BAA. The security architecture includes gVisor-based sandboxing for compute isolation, TLS 1.3 for public APIs, and encryption for data in transit and at rest.
Integration Approach for Mastra
Mastra's official sandbox providers now include Modal via @mastra/modal, alongside E2B, Daytona, Blaxel, and Vercel. Modal's GPU support is a meaningful advantage for ML-heavy agents that need capabilities other platforms may not provide.
Best For: Mastra agents that require GPU compute for ML inference, model fine-tuning, or heavy computation. Modal is a strong option for GPU-backed sandbox workloads with serverless scaling.
2. E2B
E2B specializes in secure sandboxes for AI agents, with an official @mastra/e2b package providing native integration. The platform focuses on ephemeral code execution with Firecracker microVM isolation, offering strong security boundaries for running untrusted code.
Core Capabilities
- Firecracker microVMs: Hardware-level isolation providing strong security guarantees for untrusted AI-generated code
- Official Mastra SDK: Native
@mastra/e2b package with template sandboxes, background processes, and self-hosted options - Cold starts: E2B supports cold starts, emphasizing Firecracker sandboxes and template snapshots
- Multi-language support: Python, TypeScript/JavaScript integration patterns with reproducible template environments
Mastra Integration Features
The @mastra/e2b package provides template sandboxes for standardized environments, background process management, and self-hosted deployment options for data sovereignty requirements.
Scale and Concurrency
E2B lists 20 concurrent sandboxes on Hobby and 100 on Pro by default, with the ability to purchase additional Pro concurrency up to 1,100; Enterprise limits are custom. Pro plans allow a 24-hour maximum session duration.
Best For: Mastra agents focused on CPU-based code execution and testing where security isolation is paramount and GPU acceleration isn't required.
3. Daytona
Daytona provides persistent development environments with an official @mastra/daytona SDK, making it a strong choice for Mastra agents requiring stateful workspaces. Daytona and MCP Academy materials describe provisioning large batches of sandboxes.
Core Capabilities
- Configurable lifecycle: Daytona supports persistent sandboxes and configurable lifecycle behavior. By default, Mastra's Daytona provider auto-stops after 15 minutes of inactivity and auto-archives after 7 days
- Open-source core: AGPL-licensed for self-hosted deployments with full control over infrastructure
- Container startup: Supports cold starts for container-based sandboxes
- Git and LSP integration: Native support for development workflows with devcontainer compatibility
Mastra Integration Features
The @mastra/daytona package provides snapshot capabilities for state preservation, network isolation controls, persistent volumes for data retention, and ephemeral mode for temporary workloads.
Security Considerations
Daytona documents isolated sandbox environments with OCI/Docker-compatible workflows and namespace and resource isolation. This is a lighter-weight isolation model than Firecracker microVMs.
Best For: Mastra agents requiring persistent workspaces, long-running sessions, or self-hosted deployment with open-source infrastructure.
4. Blaxel
Blaxel offers perpetual sandboxes and supports resume from standby. The official @mastra/blaxel package provides native integration with extensive runtime support.
Core Capabilities
- Resume from standby: Blaxel supports sandbox resume from standby state
- Nine runtime environments: Support for Node, Python, Bash, Ruby, Go, Rust, Java, C++, and R
- Perpetual sandboxes: Sandboxes remain on automatic standby rather than being torn down, preserving state and dependencies
- MicroVM isolation: Strong security boundaries for untrusted code execution
Mastra Integration Features
The @mastra/blaxel package supports port exposure for web services, TTL-based lifecycle management, abort signals for graceful termination, and persistent volumes for data survival across sandbox recreation.
Use Case Focus
Blaxel positions itself around "agent computers" that maintain shell history, installed dependencies, and execution context across sessions, beneficial for Mastra agents needing continuity rather than clean-room execution.
Best For: Mastra agents requiring sandbox resume from standby, multi-language runtime support, and persistent execution state.
5. RunPod
RunPod markets lower-cost GPU compute than hyperscalers, though actual savings vary by GPU, region, utilization, and pricing model. It requires custom orchestration for sandbox-style workloads. There is no official Mastra SDK, so teams must build custom integration to access RunPod's GPU pricing.
Core Capabilities
- Extensive GPU fleet: A broad GPU selection including B200, H200, H100, A100, L40S, L4, and RTX-class GPUs
- Cost-effective compute: Lower cost than hyperscalers for GPU-intensive workloads, with savings dependent on SKU, region, and pricing model
- No data egress fees: Cost advantage for data-heavy workflows
- Flexible deployment: VMs and containers on GPU nodes with custom configuration
Integration Considerations
RunPod is not optimized for sandbox-style code execution out of the box. Teams need to build custom orchestration for container lifecycle management, security isolation layers, and Mastra SDK compatibility.
Trade-offs
RunPod cold starts are workload- and image-dependent and vary with the container image and model-loading path. This makes RunPod better suited for longer-running workloads than ephemeral sandbox execution.
Best For: Teams with budget constraints on GPU compute who can invest in building custom sandbox orchestration for Mastra integration.
6. Vercel Sandbox
Vercel Sandbox provides isolated code execution environments powered by Firecracker microVMs, reaching general availability in January 2026. Mastra provides a Vercel MicroVM sandbox integration via @mastra/vercel, and the TypeScript-friendly API aligns well with Mastra's ecosystem.
Core Capabilities
- Firecracker isolation: Each sandbox runs in an on-demand Linux microVM with dedicated filesystem, network, and process space
- Ephemeral runtime model: Sandboxes designed for start-run-stop cycles with automatic persistence for filesystem state
- Developer-friendly Linux access: Sudo, package managers, and standard command-line workflows
- Vercel ecosystem integration: Native compatibility with Vercel's deployment and hosting infrastructure
Use Case Focus
Vercel Sandbox fits best for agent workflows involving repeated start-run-stop cycles, short-lived tasks, or secure execution of generated code within the broader Vercel ecosystem.
Best For: Teams already invested in the Vercel ecosystem needing isolated code execution for Mastra agents without GPU requirements.
7. Cloudflare Sandbox
Cloudflare Sandbox exposes code execution through the Sandbox SDK, supporting Python and Node.js workloads with global edge distribution. It reached general availability on April 13, 2026, and offers TypeScript-first development patterns that complement Mastra's architecture.
Core Capabilities
- Python and Node.js execution: Support for scripts, applications, code compilation, and data-processing workloads
- TypeScript-first SDK: API for sandbox lifecycle management, command execution, file operations, and WebSocket connections
- Isolated Linux containers: Dedicated filesystem and container per sandbox with configurable persistence
- Edge distribution: Built on Cloudflare Workers for global network access
Integration Patterns
Cloudflare's tutorials include AI code executor and AI coding agent examples built with the OpenAI Agents SDK, demonstrating patterns transferable to Mastra agent development.
Best For: Teams preferring Cloudflare's edge infrastructure and TypeScript-first development model for globally distributed Mastra agents.
Why Modal Stands Out for Mastra Sandbox Workloads
GPU-Capable Serverless Sandboxes
Modal combines secure sandboxed execution with GPU access. While E2B, Daytona, and Blaxel focus on CPU-based code execution, Modal pairs secure sandboxing with GPU compute. When your Mastra agents need to run ML inference, fine-tune models, or perform compute-intensive analysis, Modal is a strong serverless sandbox option.
Purpose-Built AI Infrastructure
Modal's custom-built container runtime, scheduler, and file system are optimized for AI workloads. Memory Snapshots can reduce cold start latency for initialization-heavy Functions, and the multi-cloud capacity pool improves GPU availability and provides access to the latest GPUs without quotas or reservations.
Scale Without Compromise
Modal supports 100k+ concurrent sandboxes with strong cold-start performance, scale that enables massive parallel agent evaluations and batch processing. The platform powers over 10,000 teams including production workloads at Ramp, Lovable, and Applied Compute.
Enterprise Security and Compliance
With SOC 2 Type II certification, HIPAA support on Enterprise plans via a BAA, and gVisor-based sandboxing, Modal meets enterprise compliance requirements. The platform's TLS 1.3 encryption and documented vulnerability remediation timeframes provide the security posture that production Mastra deployments demand.
Native Mastra Integration
Mastra now documents a Modal sandbox provider via @mastra/modal, so teams can adopt Modal alongside other native providers like E2B, Daytona, Blaxel, and Vercel. Modal's GPU support remains a differentiator for ML-heavy agents.
