What is an AI agent sandbox?

An AI agent sandbox is a secure, isolated environment — usually a microVM or container — where an AI agent can execute code it generated, run shell commands, install dependencies, and inspect file systems without touching your production infrastructure. It's the runtime layer for code interpreters, Codex/Claude Code agents, and any framework that lets an LLM call exec(). E2B, Modal, Daytona, Northflank, Cloudflare Sandbox, and (now) OpenAI's Ona all compete here. The risk surface is huge — running untrusted AI-generated code is one of the top security concerns in 2026.

Should I switch from E2B or Modal to Ona now that OpenAI bought it?

Not yet. As of June 13, 2026, Ona-inside-OpenAI doesn't have a published API for cross-model agents. If you only build on Codex, Ona is on the path to becoming the default — wait for the Codex Cloud announcement. If you build cross-model agents (mixing Claude Fable 5, GPT-5.5, Gemini 3.5 Pro), stay on neutral providers like E2B or Modal. E2B remains the best fit for code-interpreter style tools; Modal wins when you need GPUs for inference inside the agent loop.

Which sandbox has the fastest cold start?

As of June 2026, E2B leads on cold start (~150ms via Firecracker microVMs), followed by Cloudflare Sandbox (sub-second via V8 isolates), then Vercel Sandbox. Modal warm starts in ~200ms but cold starts are 1–3 seconds. Daytona and Northflank vary by tier. Ona's published cold-start numbers post-OpenAI are not yet public, but Gitpod-era Ona was multi-second to start a full dev environment — the agent-sandbox profile should be faster.

E2B and Modal both offer usage-based pricing with free tiers (E2B: $0 to start, pay per compute-second; Modal: $30 free credits/month plus usage). Daytona, Northflank, and Cloudflare Sandbox are also usage-based. Ona's standalone pricing is murky post-acquisition; expect Codex Cloud to bundle Ona compute into ChatGPT Pro / Business plans, which could undercut neutral sandboxes for OpenAI-only workloads but won't help cross-model builders.

Quick Answer

OpenAI Ona vs E2B vs Modal: Agent Sandboxes (June 2026)

Published: June 13, 2026

OpenAI’s June 11, 2026 acquisition of Ona reshuffles the AI agent sandbox stack. Ona joins E2B, Modal, Daytona, Northflank, Cloudflare Sandbox, Vercel Sandbox, and others in the race to be the default execution layer for autonomous AI agents. Here’s how the three most relevant choices compare for builders today.

Last verified: June 13, 2026

TL;DR

Use case	Best fit
Code interpreter / data analysis tools	E2B (Firecracker microVMs, ~150ms cold start)
GPU-bound agents (LLM inside the loop)	Modal (B200/H200/H100 access, native Python)
OpenAI Codex-only workflows	Ona (post-acquisition default)
Cross-model agents (Claude + GPT + Gemini)	Stick with E2B or Modal
Edge / low-latency at scale	Cloudflare Sandbox

The three platforms in one sentence each

Ona (OpenAI): Cloud development environments and orchestration, originally Gitpod, now becoming OpenAI’s first-party Codex execution layer. See OpenAI acquires Ona.
E2B: Agent-first Firecracker microVM sandboxes with SDKs for LangChain, LlamaIndex, CrewAI, and the OpenAI Code Interpreter pattern.
Modal: Python-native serverless platform that doubles as an agent sandbox, with strong GPU access and easy job orchestration.

Side-by-side comparison

	Ona (post-OpenAI)	E2B	Modal
Isolation	microVM + Kubernetes	Firecracker microVM	Managed containers
Cold start	TBD (Gitpod era: multi-second; agent profile likely faster)	~150ms	~1–3s cold / ~200ms warm
Persistent storage	Yes (dev-environment heritage)	Ephemeral by default; persistent FS available	Volumes; S3 mounts
GPU access	Not the focus	Limited	Yes (H100, H200, B200)
Agent framework integrations	Codex-first (post-acquisition)	LangChain, LlamaIndex, CrewAI, custom SDK	Any Python agent + Modal SDK
Pricing model	TBD (bundled into Codex?)	Usage-based, free tier	Usage-based, free $30/mo credit
Run inside customer’s cloud	Yes (Ona heritage)	Self-hosted edition available	Limited; Modal-managed by default
Open-source story	Gitpod was OSS; uncertain post-OpenAI	Partial OSS SDK	Closed core, OSS SDKs
Best for	OpenAI Codex agents at scale	Code interpreters, tool calls, multi-tenant agent runners	GPU-heavy agents, Python-native teams

When each one wins

Pick Ona (post-OpenAI) when:

You build exclusively on OpenAI Codex / GPT-5.5 / GPT-5.6.
You need long-running agents that survive a closed laptop.
You want first-party billing on your ChatGPT Pro/Business plan.
You’re an enterprise that needs Codex agents inside your own VPC.

Risk: Vendor lock-in to OpenAI. If you ever switch models, you start over.

Pick E2B when:

You build cross-model — Claude Fable 5, GPT-5.5, Gemini 3.5 Pro all in one agent.
You need Firecracker-grade isolation for hostile multi-tenant code.
Your primary use case is code interpreter style: “run this Python snippet and return the output.”
Cold-start latency matters (chat-tier UX).

Risk: Newer company than Modal; smaller GPU options.

Your agent loop includes calling models locally or running heavy Python ML.
You want exotic GPUs (B200, H200) without paying hyperscaler prices.
Your team already writes Python and likes serverless function semantics.
You want one platform for batch jobs, web endpoints, and agent sandboxes.

Risk: Cold starts hurt chat-tier UX; less agent-native than E2B.

The cross-model question

The most important question in June 2026 isn’t “which sandbox is fastest” — it’s “are you betting on one model family or multiple?”

If you’re betting on OpenAI exclusively:

Ona is the path. Wait for Codex Cloud.

If you’re betting on Anthropic exclusively:

Use Anthropic’s Claude Cowork, Agent SDK, managed Code Workflows.

If you’re building a product where users pick a model (or where you route across models for cost/quality):

Stay on neutral providers. E2B, Modal, Daytona, or Northflank.
Avoid first-party lock-in; today’s “free integration” is tomorrow’s price hike.

What the Ona deal signals for the market

Hyperscalers consolidate the agent runtime. Microsoft has its own. Google has Antigravity. AWS has AgentCore. Anthropic has Cowork. Now OpenAI has Ona. Neutral sandboxes are increasingly squeezed — they need to be 10x better at something specific (isolation, GPUs, edge) to keep growing.
Microe2VM + Kubernetes is the consensus stack. Every modern agent sandbox runs on Firecracker, gVisor, or V8 isolates with K8s orchestration. The differentiator moves to developer experience and ecosystem.
“Sandbox” is becoming a commodity; orchestration is the product. The interesting work is in agent fleets, sub-agent coordination, and persistent state — not isolation primitives. Ona’s orchestration heritage is why OpenAI paid for it.

What to watch in Q3 2026

Codex Cloud branding. Will OpenAI keep “Ona” or rebrand?
E2B fundraising / response. Watch for E2B announcing deeper Anthropic integration as a counter-move.
Modal GPU pricing. If Modal cuts B200 prices, neutral GPU-bound agents become more economical than Codex Cloud.
NVIDIA OpenShell. NVIDIA’s own AI sandbox push could compete with all of these for GPU-native agents.

Bottom line

For Codex-only enterprises, Ona is becoming the default and it’s a strong default. For cross-model agent builders, E2B is still the best agent-first sandbox and Modal is still the best GPU-friendly serverless platform. The acquisition doesn’t kill the neutral sandbox market — it just makes the choice between “all-in on one model family” and “stay neutral” more consequential.

Sources: OpenAI announcement (June 11, 2026), Ona blog (June 11, 2026), E2B docs, Modal docs, MCP Directory comparison (June 2026), AI Security Guard sandbox comparison (June 2026), Beam Cloud 2026 sandbox guide.

OpenAI Ona vs E2B vs Modal: AI Agent Sandboxes Compared