Agent37 says a standard sandbox for running an AI agent costs $4.76 for a full month, against about $249 at Vercel, $145 at Cloudflare and $121 at Daytona for the same 2 vCPU, 4 GB configuration. The figures come from Agent37's own pricing comparison, published October 10, 2026, and were repeated in a launch note on November 3. This post checks how the math is built and what it leaves out. Agent37 is the seller of the cheap option, which is the first caveat.
TL;DR: the claim and the fine print #
| Question | Answer |
|---|---|
| What is the headline price? | $4.76 for 730 running hours of 2 vCPU, 4 GB RAM, with 4 GB disk |
| Who made the comparison? | Agent37 itself ("We build Agent37") |
| When were rival prices checked? | October 10, 2026, from public pricing pages, per Agent37 |
| Is it a subscription? | No. Prepaid balance billed by the minute; monthly figure assumes continuous uptime |
| What is excluded? | Credits, plan fees, taxes, most network charges and, per the guide, model usage |
| Is it a performance benchmark? | No. Agent37 says these are price calculations, not benchmarks or identical hardware |
| Independent check? | None found; HN commenters raised competition and price-war questions |
What does Agent37 sell? #
Agent37 says it builds sandboxes for running AI agents "at under 10% of the cost of most sandbox providers." In its Launch HN post (YC F26), founder Vishnu says customers spend an average of $0.37 a month per sandbox. The company began as an OpenClaw wrapper in February and added more agent harnesses over time, including Hermes. A news summary says the platform runs harnesses such as Claude Code and Codex inside gVisor sandboxes with individual filesystems and hard disk quotas. The pitch for app builders is to give every user a permanent personal agent for tasks like building software or analyzing files, which only works economically if each agent costs very little.
For background on the agents these sandboxes host, see our comparison of Hermes Agent and OpenClaw, our guide to running Hermes on a remote VPS, and the safety discussion in Is OpenClaw safe?.
How is the $4.76 built? #
Agent37's guide sets one workload: 2 vCPU, 4 GB RAM and 730 aggregate running hours. Its own row includes 4 GB retained disk. It prices rivals at published rates for the same workload, then ranks them. Per its table:
| Provider | 730-hour estimate (Agent37's math) | Note in the guide |
|---|---|---|
| Agent37 | $4.76 | Includes 4 GB retained disk |
| Hetzner | $6.49 | A VM you operate yourself; marked unavailable when checked |
| Northflank | $48.66 | Published compute rates |
| AWS EC2 | $55.85 | DIY VM |
| Morph | $73.00 | Compute-unit rate |
| Daytona, E2B | $120.89 each | Before plan fees and storage |
| Cloudflare Sandbox | $145.28 | Uses 6 GiB RAM to meet custom-size rules |
| Vercel Sandbox | $248.78 | Assumes both CPUs busy |
The Vercel and Daytona figures follow from each provider's published rates. Vercel's Sandbox pricing page lists Active CPU at $0.128 per hour and provisioned memory at $0.0212 per GB-hour. Daytona's pricing page lists about $0.0504 per vCPU-hour and $0.0162 per GiB-hour for memory. Applied to 2 vCPUs and 4 GB over 730 hours, those rates give roughly $249 and $121.
The guide says the range across the 15 providers is more than 50x, from $4.76 to $248.78. It also lists subscriptions on top of some providers (E2B Pro adds $150 a month, Runloop Pro $250, Cloudflare requires the $5 Workers plan) and strips them out of the comparison.
Why the gap is smaller, or different, in real use #
Agent37's guide itself explains several reasons the numbers are not a like-for-like price war:
- Active-use billing. Fly.io Sprites, Cloudflare and Vercel charge for CPU only while it is busy. The $248.78 Vercel figure assumes both CPUs are busy for all 730 hours. An agent that sleeps most of the day would pay far less.
- Idle time. Agent37's own monthly number is for continuous uptime. A sandbox that sleeps pays less compute while keeping files. The guide's 62-hour column shows $0.73 for Agent37, a more typical usage pattern.
- Hardware is not identical. Isolation technology, startup time, networking and support differ. gVisor offers sandboxing at the syscall layer, while a full VM has its own kernel. Agent37's founder says in the Launch HN post that its gVisor sandboxes do not support Docker-in-Docker or Android emulators, and that it hosts full VM sandboxes at a slightly higher price for those cases.
- Model cost is separate. The guide states model usage is billed separately from infrastructure, and a sandbox balance does not include Claude inference. For a coding agent, inference often dominates cost, so a cheap sandbox shrinks only part of the bill. Compare with our posts onClaude Code token efficiency and on cheaper open models.
- Free tiers and credits. Rivals offer free allowances that the comparison excludes. The guide itself says there are cheaper ways to run a few short jobs inside another provider's free allowance.
Different listings for Agent37 even give different entry prices: a Product Hunt listing says always-on agents start from $3.44 a month, FalcoScan lists paid plans from $9 a month, and a Hacker News comment cites $4.94 for a 2 vCPU, 4 GB box. They may refer to different configurations or dates. Check Agent37's current pricing page before you plan around any one of them.
What did Hacker News say? #
The Launch HN thread (163 points, October 12) mixes praise and doubt. One user, rajangdavis, said they had used the service for months and found it easy to set up, adding that their bank had blocked a payment to Hetzner. Another, invalidOrTaken, called it great. Skeptics focused on competition: mparis suspected it would be hard to capture value in a race to the bottom against well-funded rivals that can sell sandboxes at a loss, and MikhailTal argued sandboxes are becoming commoditized and competing purely on price is a weak position. colesantiago pointed to another YC sandbox startup said to be even cheaper. olalonde noted the free tier worked without an API key and could not tell which model it used. These are commenters' views, not test results.
A worked example: three agents, three bills #
Suppose you run a product where each user has one personal agent. Take three usage patterns and apply the numbers from Agent37's own table. An agent awake 62 hours a month costs Agent37 about $0.73 by its estimate, and one that runs all month costs $4.76. At a provider that bills active CPU only, an agent that is busy for 62 hours would also pay far less than the $248.78 full-month figure, because the table assumes both CPUs are busy throughout. The gap between providers therefore shrinks as duty cycle falls, and it can reverse once plan fees apply, since a flat monthly fee dominates a small bill.
Now add the model. A coding agent that makes hundreds of calls a day can spend more on tokens than on its sandbox by a wide margin. If inference is ten times your sandbox bill, a 50x sandbox saving moves your total by a few percent, not by 50x. Do this arithmetic with your own numbers before you rebuild anything.
A gauge with a green needle near its limit, showing how agent sandbox compute cost rises with running hours
How to check any sandbox price for your own agents #
- Measure your duty cycle. How many hours a day is the agent actually running, and how many is it waiting?
- List what you need. Docker, GPU, browsers, emulators, outbound network access, persistent disk.
- Price the whole stack. Compute, storage, egress, plan fees, and model inference.
- Test isolation. For untrusted code or user-supplied prompts, ask how the sandbox separates tenants and what happens if an agent breaks out. Our post ona sandbox escape in Claude Cowork shows why this matters. For runtime controls on agents that act without a human watching,AgentBeam , the agent security platform from the explainx.ai team, stops AI agents before they take dangerous actions.
- Run a two-week trial on two providers with the same workload and compare invoices and failure rates.
- Read the terms on data retention, uptime and what happens to your files if the startup shuts down.
What this means for builders #
If you build a product where every user gets an agent, per-agent cost decides whether the business works, and sandbox price is one input. A drop from tens of dollars to a few dollars per always-on agent changes what is feasible, but only after you add model cost and support. Treat the headline as a prompt to benchmark, and treat any single-vendor comparison, including this one, as marketing until you have confirmed the numbers yourself.
For more on running agents in parallel and isolated, see our posts on [Worktrunk and Git worktrees for parallel agents](https://explainx.ai/blog/worktrunk-git-worktree-cli-parallel-ai-agents-claude-code-2026) and on [Hermes mobile](https://explainx.ai/blog/hermes-mobile-beta-nous-research-ios-android-full-after-thanksgiving-release-claimed-vs-verified-2026).
Bottom line #
Agent37's $4.76 figure is real as a list-price calculation on its own page and plausible for a gVisor sandbox. The 50x claim depends on assumptions chosen by the seller: full CPU use at rivals, continuous uptime, no credits, no model cost. Verify with your own workload before you move anything.
Prices and claims are accurate as of November 3, 2026, based on Agent37's own pages and a Hacker News thread. Providers change pricing often.