E2B and Daytona Both Charge $0.0504/vCPU-Hour. That's the Managed-Sandbox Anchor Price — Here's the Receipt

Two rival AI-sandbox vendors, two different isolation stacks, one identical price: $0.0504 per vCPU-hour and $0.0162 per GiB-hour, per second, down to the fourth decimal. E2B runs Firecracker microVMs; Daytona runs container-based isolation — and the meter converged anyway. That tells you the price was never set by the hypervisor. It was set by the unit economics of running managed, sub-second agent sandboxes at scale, and it is now the anchor every buyer and every self-hosted alternative negotiates against.

Here is the receipt in one paragraph: raw dedicated hardware rents for roughly $0.006 per thread-hour, so the $0.0504 list price carries an ~8x multiple. That gap pays for warm-pool idle headroom (sub-second boots require servers waiting around), orchestration and control planes, snapshots and egress, SLAs and support, and margin — in roughly that order. One caveat belongs in the verdict, not the footnotes: Northflank charges $0.01667 per vCPU-hour, 3x below both, so $0.0504 is the managed-duopoly anchor, not a physical floor. The rest of this post documents the convergence, follows the funding that underwrites it, and decomposes the number bottom-up so you know exactly what a self-hosted sandbox fleet has to beat.

The convergence, documented​

Both rate cards describe the same billing model: wall-clock metering, per second, for as long as the sandbox exists. E2B lists $0.000014 per vCPU-second — multiply by 3,600 and you get $0.0504 per vCPU-hour — plus $0.0162 per GiB-hour of memory. Daytona's own pricing page lists compute at $0.0504 per vCPU-hour, memory at $0.0162 per GiB-hour, and storage at $0.000108 per GiB-hour after 5 GB free. Two independent 2026 comparisons — Northflank's sandbox roundup and MarkTechPost's benchmark — tabulate both vendors at exactly these rates.

A 2 vCPU / 4 GB sandbox therefore costs $0.1656 per running hour on either platform — $120.89 for a month that never pauses. And it is not just two vendors: TokenCost's pricing analysis priced a reference 20-minute, 2 vCPU / 4 GB job at $0.055 on E2B, Daytona, and Blaxel alike, versus $0.12 inside the OpenAI Agents API. Three vendors at the same effective rate, with the hyperscaler abstraction layer above them charging 2.2x. That is what a discovered market price looks like.

The interesting part is what didn't converge. The stacks differ (microVM vs container), the plan floors differ ($150/month Pro vs no floor plus a credit), the GPU stories differ (none vs H100s), and the cold-start numbers differ (~150 ms vs sub-90 ms). When two vendors with different costs, different architectures, and different packaging land on the same rate to four decimals, the rate is not cost-plus arithmetic from either side. It is the price the market will bear for "a managed sandbox, right now, billed by the second" — set by competition, not by either vendor's BOM.

The funding behind the price​

Anchor prices need anchors, and here the anchors are two very similar Series A rounds. E2B raised $21M in July 2025, led by Insight Partners with Docker's former CEO Scott Johnston among the angels, on the back of growth from 40,000 sandboxes a month in March 2024 to 15 million a month a year later — a 375x ramp — plus the headline claim of adoption inside 88% of the Fortune 100 and 200M+ sandboxes started to date. Daytona followed with $24M in February 2026, led by FirstMark with Matt Turck joining the board, under the banner "give every agent a computer": programmatic, stateful sandboxes launching in milliseconds for everyone from YC startups to Fortune 100 enterprises.

Read the two announcements together and the investor thesis is identical: agent-scale compute demand is real, it is measured in sandbox-sessions (millions a month and climbing), and the winner is whoever turns "boot an isolated computer" into a reliable API call. That thesis is what $0.0504 monetizes. Neither round is funding cheaper hardware — it is funding the control plane, the snapshot machinery, the global footprint, and the enterprise sales motion that turn raw compute into a sandbox API. The price holds because both vendors are selling the same abstraction (per-second managed sandboxes) to the same buyer (teams whose agents need to execute untrusted code now), and neither has a reason to start a price war while demand is growing 375x year over year.

Decomposing the $0.0504​

Start from the bottom: what does the underlying compute actually cost? Take a Hetzner AX52 — Ryzen 7 7700, 8 cores / 16 threads, 64 GB DDR5, 2×1 TB NVMe — at €64/month.

That works out to €0.0055 per thread-hour, roughly $0.0063 at current rates. Memory is about €1 per GB-month, or ~$0.0016 per GiB-hour. Against the $0.0504 / $0.0162 list rates, the multiples are ~8x on CPU and ~10x on RAM.

Before crying margin, run the sensitivity on the variable that actually drives the number: pool utilization. Nobody's agent waits 45 seconds for a cold VM; both vendors promise boots in milliseconds to ~150 ms, which means warm capacity sitting idle. At 100% utilization the hardware share is $0.0063 (12% of list). At 30% utilization — a plausible warm pool serving bursty agent traffic — the hardware share alone is $0.021, or 42% of list. At 20% it is $0.0315, nearly two-thirds. Neither vendor publishes pool utilization, so treat those as a sensitivity band, not a disclosure — but the band tells the story: idle headroom for instant boots is very plausibly the single biggest line inside the $0.044 gap.

The rest of the gap, in rough order:

• Orchestration and control plane. Scheduling millions of sessions a month, per-second metering, snapshot create/restore, network policy per sandbox — this is a distributed system with on-call, not a for-loop over VMs.
• Snapshots and storage. E2B includes 10–20 GB per sandbox; Daytona meters storage past 5 GB free. Somebody pays for the NVMe behind every template, snapshot, and paused sandbox.
• Egress and footprint. Sandboxes that fetch models, clone repos, and push artifacts burn bandwidth in regions the customer chose, not the cheapest one.
• SLA, support, and compliance. The Fortune-100 buyer behind both vendors' enterprise motion pays for SOC 2 reports and a status page with somebody else's pager attached.
• Margin. Whatever is left — and with Northflank at 3x below, visibly less than "whatever the market will bear" everywhere.

The memory multiple (~10x) is arguably the purer read on managed margin than the CPU multiple (~8x): RAM cannot be oversubscribed the way CPU can, so the memory line carries less utilization distortion and more of the true service markup. Either way, the receipt says the same thing: you are not buying compute at $0.0504. You are buying instant, isolated, metered compute, and the adjectives cost 7–9x the noun.

The honest caveats​

Three facts keep this from being a two-vendor commercial. First, the anchor is not the floor: Northflank's 2026 comparison lists its own compute at $0.01667 per vCPU-hour and $0.00833 per GB-hour — 3x under the duopoly rate — with GPUs (L4 through H200) on the same bill. Any self-host business case should benchmark against Northflank, not just E2B and Daytona.

Second, the plan floors change small-scale math completely. E2B's $150/month Pro fee is real money on top of usage — at prototype scale it can be the biggest line on the invoice — while Daytona charges no floor and opens with a $200 credit. Two identical meters with different cover charges are not the same deal until usage amortizes the fee.

Third, the meters are only comparable because both are wall-clock. The moment your agent idles — model round-trips, human approvals, long polls — active-CPU billing (Vercel Sandbox, Fly Sprites) changes the answer. We worked the full crossover math in yesterday's comparison: below ~32% CPU-active time, idle-free billing wins; above it, the flat $0.0504 wins by a widening margin. Read that post before migrating on headline rates.

What it means for self-hosting​

The decomposition above is also a shopping list. A self-hosted sandbox fleet that bin-packs onto owned hardware starts from ~$0.006 per thread-hour instead of $0.0504 — the same AX52 that anchors the receipt fits eight 2 vCPU / 4 GB sandboxes at roughly $9 per sandbox-month against $120.89 on either meter.

That ~8x headroom is your budget for everything the vendors do: warm pools, snapshot machinery, metering, and whoever carries the pager. Spend less than 8x on those and self-hosting wins on unit cost. The honest question is whether your utilization and your ops capacity clear that bar — not whether the hardware is cheaper. It obviously is.

Both vendors, notably, will sell you the shovel: E2B's infrastructure is open source and the company offers deploy-in-your-cloud and on-premise options, while Daytona ships Helm/K8s self-hosting for its container-based stack. That is the tell that the $0.0504 is a managed-service price, not a compute price — both vendors are happy to unbundle the software from the meter.

Renting still wins in two shapes: spiky burst (a thousand sandboxes for an hour beats owning a thousand cores all month) and zero-ops teams (no pager, no pool tuning, no snapshot retention to design). But if your sandboxes run hot and steady — CI-shaped agent fleets, always-on dev environments, bulk eval harnesses — the receipt says the meter is 8x the metal, and the metal is a solved problem.

The $0.0504 convergence is the market telling you managed sandboxes have a standard price. Whether you pay it, undercut it with Northflank, or delete it with owned hardware depends on your utilization curve — so measure that before you sign anything. When bex's own E2B-style sandbox story lands on bin-packed Hetzner capacity, this receipt is the benchmark it will be graded against.

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