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Best AI agent sandboxes and compute platforms in 2026

A practical guide to choosing infrastructure for AI agent workloads.

The number of platforms targeting AI agent infrastructure has exploded. Choosing the right one depends on what your agent actually needs: fast ephemeral code execution, persistent VMs, GPU access, edge deployment, or fully autonomous self-provisioning.

This guide covers the major options, what each is best at, and where each falls short.

E2B — The code execution sandbox leader

E2B is the most established AI agent sandbox. It uses Firecracker microVMs for fast, isolated code execution. Python and TypeScript SDKs. Open-source core. Claims 88% of Fortune 100 have signed up.

Best for: Short-lived code execution — run a snippet, get a result, discard the environment. Coding agents, deep research agents, and any workflow where the agent generates and runs code in a loop.

Limitations: Requires human account setup. Not designed for persistent or long-running workloads. SDK-dependent. Enterprise-focused pricing.

Pricing: Usage-based per sandbox minute. Free tier with limited minutes.

Daytona — Fastest cold start, security-first

Daytona raised $24M in Feb 2026 to build "agent-native compute infrastructure." Sub-90ms cold starts. Positioned around secure execution of AI-generated code. "Give every agent a computer."

Best for: Agents that need the fastest possible sandbox boot time and strong isolation guarantees. Security-sensitive code execution workflows.

Limitations: Still requires human account setup. Focused on ephemeral execution, not persistent infrastructure. Newer platform — ecosystem is still maturing.

Pricing: Usage-based. Details vary by plan.

Modal — GPU-first serverless for AI

Modal raised $80M and positions as "AI infrastructure that developers love." Python-first serverless with strong GPU support. Sub-second cold starts. Not agent-specific, but widely used for AI workloads.

Best for: GPU-heavy AI workloads — model inference, fine-tuning, batch processing. Python developers who want serverless without Docker.

Limitations: Python-only. Not designed for agent self-provisioning. Requires human account and CLI setup. Pricing can be unpredictable for variable workloads.

Pricing: Per-second compute billing. Free tier available.

Fly.io — General-purpose cloud pivoting to agents

Fly.io offers Machines (full VMs) and the newer Sprites (persistent VMs designed for agent workloads). Firecracker-based. Good edge distribution. CLI-first developer experience.

Best for: Developers who want VM-level control with global edge deployment. Sprites are interesting for persistent agent compute, though the feature is still early.

Limitations: Requires human account and CLI install. Not designed for agent-initiated signup. Edge focus adds complexity for simple use cases.

Pricing: Per-second Machine pricing. Free tier with limited resources.

Cloudflare Workers + Sandbox SDK — Edge with isolation

Cloudflare's Sandbox SDK runs under the Workers/Agents umbrella. V8 isolates for edge code execution, with a sandbox layer for untrusted agent workloads. Massive global network.

Best for: Lightweight, request-driven agent workloads at the edge. If your agent generates small code snippets and needs global low-latency execution, Workers is hard to beat.

Limitations: V8 isolates only — no system access, no SSH, no arbitrary binaries. Execution time limits. Requires human Cloudflare account. Not suitable for persistent or heavy workloads.

Pricing: Generous free tier (100K requests/day). Paid plans per-request.

Agent Cloud — Self-provisioned VMs for autonomous agents

Agent Cloud (that's us) takes a different approach: the agent is the customer. AI agents can discover the product, create their own account via API, receive a sandbox key, and provision full Linux VMs — all without human intervention.

Best for: Autonomous agent workflows where the agent needs to provision its own compute. Persistent workloads, development environments, multi-step tasks, MCP server hosting, and anything that needs a full Linux VM with SSH access.

Limitations: Full VM provisioning is slower than microVM boot (minutes vs milliseconds). Not optimized for rapid ephemeral code execution. Bootstrapped — smaller scale than well-funded competitors.

Pricing: Free sandbox (1 micro VM, 72h, no card). Starter plans from $25/mo.

Try the quickstart | vs E2B | vs Daytona

Others worth knowing

• Agentuity — "Full-stack platform for AI agents" with intelligent routing and persistent state. Launched v1 in Feb 2026. Broader scope than pure compute — includes build, deploy, and monitor.
• OpenClam — "Autonomous compute for autonomous agents." The only other platform designed for agents-as-customers. Accepts stablecoin payments. Very early stage.
• Railway — "Ship software peacefully." Simple PaaS with strong DX. Not agent-specific but usable for agent workloads if a human sets up the account. $100M raise.
• RunPod / Vast.ai — GPU rental marketplaces. Popular in the community for inference and training. Not agent-native but widely used.

Quick comparison

How to choose

• Need fast ephemeral code execution? → E2B or Daytona
• Need GPUs? → Modal or RunPod
• Need edge deployment? → Cloudflare Workers or Fly.io
• Need your agent to provision its own infrastructure? → Agent Cloud

Read more about what agent-native cloud means and why it's a distinct category.