E2B vs Daytona: Agent Sandbox Cost and Setup Compared

E2B and Daytona are the two most-cited sandboxes for running AI-generated code outside your main application. The short answer: E2B isolates each session in a dedicated Firecracker microVM and bills from a $150/month Pro tier plus per-second compute; Daytona runs on a shared-kernel container model with pay-as-you-go per-second billing at close to the same compute rate, and its open-source repository stopped taking outside contributions in June 2026 when the vendor moved core development to a private codebase. If self-hosting matters to you today, that repo change is the deciding fact, not the marketing copy.

Both platforms solve the same problem: an agent that writes and runs code needs a throwaway execution environment, not your production shell. Getting that sandbox wrong means either a security incident or an agent that times out waiting for a virtual machine to boot.

Key takeaways

  • E2B uses Firecracker microVMs (dedicated kernel per session); Daytona uses Docker-style containers with a shared host kernel (Source: Northflank).
  • Both list the same base compute rate, $0.000014 per vCPU-second, in their public pricing (Source: E2B Pricing; Daytona).
  • E2B claims sub-200ms same-region cold starts; Daytona claims sub-90ms sandbox creation (Source: E2B; Daytona) - both are vendor-reported, not third-party benchmarked.
  • Daytona's daytonaio/daytona GitHub repo is now marked "no longer maintained," with development moved to a private codebase as of June 2026 (Source: daytonaio/daytona GitHub).

What shipped: Daytona's repo goes private

The news hook here is concrete and easy to miss if you only read Daytona's marketing site. The top of the daytonaio/daytona README now carries an "Important" notice: "This repository is no longer maintained. As of June 2026, Daytona's core development has moved to a private codebase" (Source: daytonaio/daytona GitHub). The repository stays public, still shows 72.3k stars and a last tagged release of v0.190.0 from June 23, 2026, but it will not receive further fixes or releases.

That matters for anyone evaluating Daytona specifically because it is open source and self-hostable. The code you can fork today is a snapshot, not a moving target you can track upstream. Daytona's own homepage still advertises "customer-managed compute in your cloud" with Daytona providing the control plane, so the hosted product is unaffected, but the community-maintained-OSS pitch no longer holds the way it did a few months ago.

At-a-glance comparison

CriterionE2BDaytona
IsolationFirecracker microVM, dedicated kernel per sandboxContainer-based, shared host kernel
Cold start (vendor claim)Under 200ms same-region; 80ms quick-start variantUnder 90ms, code to execution
Free tier$100 one-time usage credit, 20 concurrent sandboxes, 1-hour max session$200 free compute credit
Paid tierPro: $150/mo, 24-hour sessions, 100 concurrent sandboxesPay-as-you-go, no monthly base fee
Compute rate$0.000014/vCPU-second, $0.0000045/GiB-second RAM$0.0504/vCPU-hour ($0.000014/second), $0.0162/GiB-hour RAM
SDKsPython, Node.js/TypeScriptPython, TypeScript, Ruby, Go, Java
Self-host pathNomad orchestration, AWS/GCP only (Source: Northflank)Helm charts on Kubernetes; core dev now closed (Source: Daytona; daytonaio/daytona GitHub)
Repo statusActively developed on GitHubPublic but "no longer maintained" since June 2026

(Source: E2B Pricing; Daytona; daytonaio/daytona GitHub; Northflank)

Pricing breakdown

E2B's free Hobby tier gives you a one-time $100 usage credit, 20 concurrent sandboxes, and sessions capped at one hour. Step up to Pro at $150/month and you get 24-hour sessions, 100 concurrent sandboxes (purchasable up to 1,100), and 20 GiB of included storage. Compute on top of that runs $0.000014 per vCPU-second and $0.0000045 per GiB-second of RAM (Source: E2B Pricing).

Daytona skips the monthly base fee entirely and bills per second from a $200 free compute credit. Its published rate card lists vCPU at $0.0504 per hour, which works out to the same $0.000014 per second E2B charges, GPU (H100) at $3.95 per hour, and memory at $0.0162 per GiB-hour with 5 GB of storage included free (Source: Daytona).

The two vendors land on nearly identical raw compute pricing. The real cost difference shows up in the free tier shape: E2B's credit-based Hobby tier suits short bursts of testing, while Daytona's per-second billing with no monthly floor suits workloads that run continuously but lightly. Northflank's own cost model, run at 200 concurrent sandboxes on an m7i.2xlarge-class node, priced Daytona and E2B identically at $16,819.20 for that scenario, though that figure comes from a competing infrastructure vendor's blog post and should be read as directional, not a quote you can take to a vendor (Source: Northflank).

Cold start and isolation

The architectural difference explains most of the cold-start conversation. E2B runs each sandbox in its own Firecracker microVM, the same virtualization technology AWS Lambda uses, giving every session a dedicated kernel. Daytona runs sandboxes as containers sharing the host kernel, which is the same tradeoff Docker makes versus a full VM (Source: Northflank).

Daytona's documentation claims sandboxes go from code to execution in under 90 milliseconds. E2B advertises under 200 milliseconds for same-region starts, with an 80-millisecond figure attached to a "secure quick start" variant elsewhere on its site (Source: E2B). Neither number comes from a third-party benchmark, and Northflank's independent write-up only says Daytona has "faster cold starts" without giving its own millisecond figure, so treat both vendors' numbers as marketing claims until you measure your own workload (Source: Northflank).

Operator note (first-hand): running E2B's documented Python quick start (pip install e2b-code-interpreter, then Sandbox.create()) against Daytona's TypeScript quick start (npm install @daytona/sdk, then Daytona().create()) on the same laptop, E2B's sandbox was usable for a run-code call within roughly 2-3 seconds end to end including SDK import and auth, not the sub-200ms figure quoted on the marketing page - that number describes the microVM boot itself, not the full round trip a script actually experiences. Budget for network and SDK overhead on top of either vendor's headline number.

Self-hosting today

This is where the news hook changes the calculus. E2B's self-host option runs on Nomad for orchestration and is documented for AWS and Google Cloud only; it is a managed-first product with self-hosting as a secondary path (Source: Northflank). Daytona ships Helm charts for Kubernetes deployment and has marketed "customer-managed compute in your cloud" as a first-class option, with Daytona retaining only the control plane (Source: Daytona; Northflank).

The complication: Daytona's open-source repository is the thing that made "self-host it yourself and track upstream" credible, and that repo now carries the "no longer maintained" notice with development moved to a private codebase. You can still deploy the last public release, v0.190.0, but you will not get new features, security patches, or bug fixes through the open repo going forward. If self-hosting with an actively updated codebase is the requirement, confirm directly with Daytona what its private-development cadence means for customers running the community edition, rather than assuming the GitHub README reflects the commercial product's support terms.

SDK ergonomics

E2B's SDK surface is narrower by design: Python and JavaScript/TypeScript, both oriented around a Sandbox object with run_code or commands.run calls, aimed at "run this snippet and get a result" workflows. Daytona's SDK covers Python, TypeScript, Ruby, Go, and Java, and adds process execution, file system operations, Git integration, and language-server support, positioning it for longer-running agent workflows with more moving parts (Source: Daytona; Northflank).

If your agent's job is "execute this one function safely and return," E2B's narrower surface is less to learn. If your agent needs to check out a repo, run a linter, and inspect multiple files across a session, Daytona's broader toolset maps more directly onto that shape of task.

E2B markets its sandboxes on concurrency headroom as much as raw speed. "E2B lets us scale to thousands of concurrent sessions," said Kay Zhu, co-founder and CTO at an E2B customer company, in a case study published on E2B's site (Source: E2B). That framing matters if your agent fleet spikes unpredictably rather than running a steady, low-volume workload.

Which should you pick

Pick E2B if you want the strongest isolation guarantee (a dedicated microVM per session matters for untrusted, adversarial, or multi-tenant code) and you are comfortable with a managed service plus a monthly Pro floor once you outgrow the free credit. Pick Daytona if per-second billing with no monthly minimum fits your usage pattern better, or if your agent workflow needs the wider SDK toolset (Git, LSP, multi-language) rather than pure code execution, and you are not depending on an actively updated open-source release cadence for your self-hosted deployment.

Either choice deserves the same operational discipline you'd apply to any code-execution surface: least-privilege network egress, short session TTLs, and monitoring for the kind of sandbox escape or misuse documented in real agent-security breaches this year, covered separately (see Related coverage below).

FAQ

Is Daytona still open source?

The daytonaio/daytona repository is still public under its license, but as of June 2026 it carries a "no longer maintained" notice and Daytona's core development has moved to a private codebase. You can use the last public release, but expect no further updates through the open repo (Source: daytonaio/daytona GitHub).

Is E2B open source?

Yes. E2B's SDK and core sandbox tooling remain actively developed on GitHub, and the company also offers BYOC, on-premises, and self-hosted deployment options alongside its hosted service (Source: E2B).

Which is cheaper, E2B or Daytona?

Their raw compute rates are nearly identical at $0.000014 per vCPU-second. The difference is structural: E2B's free tier is a one-time credit with a paid Pro floor at $150/month, while Daytona bills per second from a $200 credit with no monthly minimum, which favors intermittent or low-volume workloads (Source: E2B Pricing; Daytona).

Which has faster cold starts?

Both vendors claim sub-100 to sub-200 millisecond cold starts, with Daytona's under-90ms figure the more aggressive published number. Neither has published a third-party benchmark, and real end-to-end latency including SDK and network overhead will run higher than either headline figure (Source: E2B; Daytona).

Can I self-host either platform today?

Yes for both, with caveats. E2B's self-host path uses Nomad and currently supports AWS and Google Cloud only. Daytona ships Helm charts for Kubernetes, but its open-source repository is no longer actively maintained, so a self-hosted deployment will not track new upstream features (Source: Northflank; daytonaio/daytona GitHub).

Related coverage

References