TL;DR: If you just need to ship fast, E2B has the best SDK experience. If you need the fastest cold starts, Blaxel wins at 25ms. For GPU workloads, Modal is unmatched. For self-hosted control, Daytona is open-source with a managed option. For persistent long-running sessions, Fly.io Sprites gives you 100GB NVMe per sandbox.
Coding agents write and execute code without you reviewing every line. Claude Code, Codex, Devin, and dozens of open-source agents all need somewhere to run that code safely. If your agent executes in an unsandboxed environment, it can access credentials, make external requests, consume unbounded resources, or exploit kernel vulnerabilities to escape entirely.
Regular Docker containers are not enough. They share the host kernel -- one kernel bug and untrusted code breaks out. Purpose-built sandboxes use microVMs or user-space kernel interception to put a hard boundary between agent code and everything else.
Platforms like Nebula run agent tasks in isolated environments precisely because unsandboxed code execution is the fastest way to turn an AI agent into a security incident. The sandbox you pick determines your security ceiling, your cold-start latency, and your bill.
Here are the five best options available today.
Quick Comparison
| Feature | E2B | Daytona | Modal | Fly.io Sprites | Blaxel |
|---|---|---|---|---|---|
| Isolation | Firecracker microVM | Isolated runtime | gVisor | Firecracker microVM | microVM |
| Cold start | ~150ms | ~90ms | Sub-second | 1-12s | ~25ms |
| Session limit | 24h (Pro) / 1h (Free) | Unlimited | 24h | Unlimited | Unlimited |
| GPU support | No | Yes | Yes (extensive) | No | No |
| Self-host | Open-source (limited) | Open-source + managed | No | No | No |
| SDK languages | Python, TypeScript | Python, TypeScript | Python (JS/Go beta) | -- | Python, TypeScript |
| Hourly cost (1 vCPU) | ~$0.083 | ~$0.083 | ~$0.119 | Pay-per-use | ~$0.083 |
| Free credits | $100 | $200 | Usage-based | Pay-per-use | $200 |
E2B -- Best for Fast Integration
E2B is built specifically for AI agent code execution, and it shows. The Python and TypeScript SDKs are clean and well-documented. Boot times sit around 150ms with Firecracker microVM isolation handling workload separation at the hypervisor level. It integrates directly with LangChain, OpenAI, and Anthropic tooling, making it one of the fastest paths from "I have an agent" to "my agent runs code safely."
Perplexity used E2B to implement advanced data analysis for Pro users in a week. Hugging Face uses it to replicate DeepSeek-R1.
Strength: Best-in-class developer experience and ecosystem integrations. If you use LangChain or the OpenAI SDK, E2B slots in with minimal code.
Weakness: Session cap of 24 hours on Pro (1 hour on Free). Self-hosting exists but is not production-ready for most teams. BYOC is AWS-only and enterprise-gated.
Best for: Teams building AI coding agents who want the fastest integration path and do not need sessions longer than 24 hours.
Pricing: Free tier with $100 one-time credit. Pro at $150/month with 24-hour sessions. Usage at ~$0.083/vCPU-hour.
Daytona -- Best for Self-Hosted Control
Daytona started as a development environment manager and has evolved into a full AI sandbox platform. The standout feature is that it is open-source -- you can run it on your own infrastructure without enterprise gatekeeping. The managed cloud option offers 90ms sandbox creation, which is among the fastest available.
Daytona goes beyond basic code execution. It includes native Git integration, LSP (Language Server Protocol) support, file system operations, and even computer use capabilities (Linux, macOS, Windows desktops). LangChain's team used Daytona to unblock their coding agent when they hit sandbox limitations.
Strength: Open-source transparency, self-hosted option, GPU support, and the broadest feature set (Git, LSP, Docker-in-Docker). Sub-90ms cold starts on managed cloud.
Weakness: The breadth of features means a steeper learning curve compared to E2B's focused SDK. The open-source version requires infrastructure expertise to run.
Best for: Teams that need self-hosted sandboxes, GPU access, or full development environment capabilities inside the sandbox. Also strong for compliance-sensitive workloads.
Pricing: $200 in free compute. Usage at $0.0504/vCPU-hour + $0.0162/GiB-hour (effectively ~$0.083/hour for 1 vCPU + 2GB).
Modal -- Best for GPU and ML Workloads
Modal is a Python-first serverless platform where sandboxes exist alongside a broader ML infrastructure stack. If your agent needs to execute code that involves GPU inference, model fine-tuning, or heavy data processing, Modal is the only option here that handles all of it natively.
It scales to 20,000 concurrent containers with sub-second cold starts and uses gVisor for isolation. Companies like Lovable and Quora run millions of executions through it. The tradeoff is the SDK model -- environments are defined through Modal's Python library rather than arbitrary container images.
Strength: Unmatched GPU support alongside sandboxing. If your coding agent generates ML code, Modal lets it run end-to-end without leaving the platform.
Weakness: Python-first means TypeScript is beta-only. gVisor isolation is lighter than Firecracker microVMs -- sufficient for trusted code, but not as strong for fully untrusted execution. No self-hosting or BYOC option.
Best for: Python-heavy coding agents running alongside ML workloads, data analysis pipelines, and teams already invested in the Modal ecosystem.
Pricing: Usage-based, billed per second. CPU from ~$0.119/vCPU-hour. GPU billed separately. No upfront commitment.
Fly.io Sprites -- Best for Persistent Sessions
Fly.io Sprites runs on Firecracker microVMs with a killer feature: 100GB persistent NVMe storage per sandbox and checkpoint/restore in around 300ms. The idle billing model stops charging when the environment is not in use, making it cost-effective for coding agents that need a warm environment between sessions.
This is the closest thing to giving your agent a persistent development machine. It can write files, install dependencies, checkpoint its state, and resume exactly where it left off.
Strength: Persistent state with 100GB NVMe, checkpoint/restore, and idle billing. The best option for agents that maintain long-running projects across multiple sessions.
Weakness: Cold starts of 1-12 seconds are the slowest on this list. No GPU support. No BYOC option. Still early-stage compared to E2B and Modal.
Best for: Long-running coding agent sessions, Claude Code-style persistent development environments, and teams building agents that work on multi-day projects.
Pricing: Pay-per-use based on CPU, memory, and storage. Idle sandboxes do not incur compute charges.
Blaxel -- Best for Ultra-Fast Cold Starts
Blaxel is the newest entrant on this list, but it leads on one critical metric: 25ms standby resume time. For applications where latency between agent requests matters -- interactive coding assistants, real-time code evaluation, or high-throughput eval pipelines -- those milliseconds add up.
Blaxel uses microVM isolation and supports both Python and TypeScript SDKs. Sessions run indefinitely with snapshot support for saving and restoring environment state.
Strength: The fastest cold start of any sandbox on this list at ~25ms. Unlimited session length. Snapshot support for stateful workflows.
Weakness: Newer platform with a smaller community and fewer case studies than E2B or Modal. No GPU support. No self-hosting option.
Best for: Latency-sensitive agent applications, high-throughput evaluation pipelines, and teams that need interactive-speed code execution.
Pricing: $200 in free credits. Usage at ~$0.083/vCPU-hour (comparable to E2B and Daytona).
How to Choose
The decision tree is simpler than it looks:
- Need GPU for ML workloads? Modal is the only real option.
- Need self-hosted or open-source? Daytona. Nothing else comes close.
- Need the fastest integration with existing AI frameworks? E2B has the best ecosystem.
- Need persistent state across sessions? Fly.io Sprites with 100GB NVMe.
- Need the lowest latency? Blaxel at 25ms resume.
- Budget-conscious? E2B ($100 credits) and Daytona/Blaxel ($200 credits) all have generous free tiers.
The Verdict
There is no single winner here -- the right sandbox depends entirely on what your agent does and where it runs. E2B is the safest default for most teams starting today: the SDK is mature, the integrations are broad, and 150ms cold starts are fast enough for almost everything. But if your requirements skew toward GPU, self-hosting, persistence, or ultra-low latency, one of the other four will serve you better.
The one thing all five agree on: if your coding agent runs in an unsandboxed environment, you are one hallucination away from a production incident. Pick one and ship.
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