AI Sandbox pricing comparison (2026)

Finding the cheapest AI sandbox provider requires more than comparing headline CPU rates. The most affordable sandbox provider for your use case depends on billing model, idle behaviour, deployment model, and whether GPU access is required.

This article covers PaaS rates, billing model differences, GPU pricing, BYOC costs, and a cost comparison at scale (using 200 concurrent sandboxes as a worked example).

AI sandboxes are isolated execution environments used to run untrusted or AI-generated code safely, without risking the host system or other tenants. They are used across AI agent workflows, code execution products, reinforcement learning pipelines, and multi-tenant platforms where user-submitted code needs to run in isolation.

Northflank sandboxes use microVM-based isolation (Kata Containers and gVisor depending on the underlying infrastructure), supporting both ephemeral and persistent environments in managed cloud or your own VPC.

The table below shows PaaS pricing where you use each platform's hardware directly. The rates vary more than they appear to at first glance, partly because billing models differ. The section that follows explains those differences in detail.

Pricing as of May 2026. Verify current rates on each platform's pricing page before making cost decisions.

Two notes on specific platforms: Modal sandbox CPU rate is approximately 3x Modal's standard compute rate, so sandbox compute is priced differently from standard Modal Functions. Vercel Sandbox memory is billed on provisioned resources for the full sandbox duration, not active usage only.

The billing model a platform uses matters more than the headline CPU rate. Two platforms with similar per-hour rates can produce very different bills depending on when the meter starts and stops, and which resources are included in the base price.

Some platforms only charge for the time the sandbox is actively using the CPU. Fly.io Sprites, for instance, uses this model with no charge when the sandbox is idle. The distinction matters for agentic workloads where sandboxes often spend significant time waiting on I/O between active execution bursts.

Vercel Sandbox, for instance, bills Active CPU only (time spent waiting for network requests, database queries, or API calls does not count toward CPU charges). However, memory is billed based on provisioned resources for the full duration the sandbox runs, not active usage. A sandbox waiting on an LLM API call pays for provisioned memory but not CPU during that wait.

Blaxel, for instance, does not publish separate CPU and memory rates. Pricing is based on memory tier: XS (2GB) at $0.0828/hr, S (4GB) at $0.1656/hr, M (8GB) at $0.3312/hr, L (16GB) at $0.6624/hr, and XL (32GB) at $1.3248/hr, all billed per second. CPU is bundled into the tier. This simplifies cost estimation when memory requirements are fixed but makes direct comparison with per-vCPU rates from other platforms harder.

Modal, for instance, bills per physical core for sandbox compute, where one physical core equals 2 vCPU. The sandbox CPU rate of $0.1419/physical core-hr is higher than it appears when compared to per-vCPU rates from other platforms. Modal's sandbox CPU rate is also approximately 3x its standard compute rate, meaning sandbox compute is priced differently from standard Modal Functions. Always convert to a common unit before comparing headline numbers across platforms.

Cloudflare Sandbox, for instance, has pricing determined by the underlying Containers platform. Compute is billed at active CPU rates, but you also pay for Workers requests and Durable Objects on top of container costs, and a $5/month Workers Paid plan is required before any sandbox usage. The total cost of a Cloudflare Sandbox deployment is the sum of multiple billing dimensions, not a single rate.

Finding the most affordable AI sandbox provider requires looking beyond the headline CPU rate. Billing models, idle behaviour, and deployment model all affect what teams actually pay at scale, making a direct cost comparison essential.

On PaaS, Northflank has the lowest published CPU rate at $0.01667/vCPU-hr, billed per second. This is significantly lower than E2B at $0.0504/vCPU-hr, Daytona at $0.0504/vCPU-hr, Fly.io Sprites at $0.07/CPU-hr, and Modal at $0.1419/physical core-hr (2 vCPU equivalent). At 200 concurrent sandboxes on the same workload specification, Northflank PaaS costs $7,200 versus $16,819 on E2B and Daytona, $24,491 on Modal, and over $35,000 on Fly.io Sprites.

For teams evaluating low-cost AI sandbox infrastructure at scale, BYOC changes the calculation further. Northflank is the only platform in this comparison offering self-serve BYOC with publicly available pricing. Teams running sandboxes inside their own cloud account pay their cloud provider directly plus a Northflank management fee, bringing the total cost for 200 sandboxes down to $2,060 compared to $7,200 on Northflank PaaS.

The most cost-effective AI sandbox option at any given scale depends on workload pattern, idle behaviour, and whether GPU access is required. For CPU-only workloads at scale, Northflank is consistently the lowest cost option in this comparison across both PaaS and BYOC.

Most platforms in this comparison do not provide GPU access within sandboxed environments, as covered in detail in GPU sandboxes explained. Northflank and Modal are the two platforms that do and publish GPU rates.

Northflank's GPU pricing covers GPU, CPU, and RAM as a combined rate per hour for GPU workloads. Modal charges GPU, CPU, and memory as separate line items, all billed per second.

Headline rates tell a partial story. The cost difference between platforms becomes much more significant at volume. The table below shows total cost for 200 concurrent sandboxes on a PaaS deployment model, based on an nf-compute-100-4 plan on an m7i.2xlarge infrastructure node.

Pricing as of May 2026. Verify current rates on each platform's pricing page before making cost decisions.

For teams running sandboxes inside their own cloud account, BYOC changes the cost structure significantly. On Northflank BYOC, the same 200 sandboxes cost $2,060 in total, compared to $7,200 on Northflank PaaS. Northflank is the only platform in this comparison offering self-serve BYOC with publicly available pricing.

For teams running sandboxes at scale, BYOC can change the cost structure significantly. Rather than paying a per-sandbox vendor rate, teams pay their cloud provider directly and a platform management fee. The table below covers BYOC availability and terms across platforms in this comparison.

Northflank is the only platform in this comparison with self-serve BYOC and publicly available pricing. All other BYOC options require a sales process, with no published rates.

With the tables and billing model differences in context, a few patterns are worth calling out for teams modelling real-world costs.

• Idle behaviour: Fly.io Sprites charges nothing when idle, with the filesystem preserved. E2B allows indefinite pause with only storage costs accruing while paused. How a platform handles idle time significantly affects cost for agent workloads that remain provisioned between sessions.
• The Modal physical core distinction: Modal's $0.1419/physical core-hr equates to approximately $0.071/vCPU-hr, which is still higher than E2B's $0.0504/vCPU-hr but not as high as the headline number suggests. The sandbox rate is also 3x Modal's standard compute rate, which matters if you are comparing sandbox pricing against other Modal workloads on the same account.
• Cloudflare's layered cost structure: The $0.072/vCPU-hr active CPU rate is not the total cost. Workers requests, Durable Objects, and the $5/month base plan all contribute. Teams building on Cloudflare Sandbox should model the full cost across all billing dimensions before comparing against single-rate platforms.

Northflank is the cheapest AI sandbox provider in this comparison on both PaaS and BYOC. On PaaS, Northflank has the lowest published CPU rate at $0.01667/vCPU-hr, billed per second. E2B and Daytona are next at $0.0504/vCPU-hr, followed by Fly.io Sprites at $0.07/CPU-hr and Modal at $0.1419/physical core-hr (2 vCPU equivalent). On BYOC, Northflank is the only platform in this comparison with self-serve access and publicly available pricing, making it the lowest cost option at scale across both deployment models.

It depends on the platform. Fly.io Sprites uses per-second active billing with no charge when the sandbox is idle. E2B allows indefinite pause with only storage costs accruing while paused. Vercel charges active CPU only but bills provisioned memory for the full duration. Always confirm whether a platform bills for the full sandbox duration or only active compute time before modelling costs for your workload.

Northflank and Modal both support GPU workloads within sandboxed environments and publish GPU pricing. Most other platforms in this comparison do not provide GPU access in sandboxes. See GPU sandboxes explained for a technical breakdown of why most platforms are CPU-only and how GPU sandbox isolation works.

BYOC (Bring Your Own Cloud) allows teams to run sandbox infrastructure inside their own cloud account. Instead of paying a per-sandbox vendor rate, teams pay their cloud provider directly and a management fee to the platform. At scale, this can reduce total cost significantly. Northflank is the only platform in this comparison offering self-serve BYOC with publicly available pricing. All other BYOC options require a sales process.

Modal prices sandbox compute at approximately 3x its standard compute rate. Sandbox CPU is $0.00003942/core/sec versus $0.0000131/core/sec for standard compute. Memory is also priced differently for sandboxes. The GPU rate for sandboxes follows Modal's standard GPU pricing. This means sandboxes on Modal cost more per unit of compute than standard Modal Functions.

The following articles cover topics referenced in this piece in more depth.

• GPU sandboxes explained: why most sandbox platforms are CPU-only, how GPU sandbox isolation works, and which platforms support GPU workloads
• Top BYOC AI sandboxes: platforms that support bring-your-own-cloud deployment with comparison across access model, clouds supported, and pricing
• Best persistent sandbox platforms: comparison of platforms that support persistent sandbox environments and how they handle idle state
• E2B vs Modal vs Fly.io Sprites: detailed comparison across isolation model, GPU support, persistence, and BYOC
• Top AI sandbox platforms for code execution: broader platform overview including isolation models, startup times, and use cases
• Best code execution sandbox for AI agents: ranked comparison of sandbox platforms for agent workloads
• Ephemeral sandbox environments: when to use ephemeral vs persistent sandbox design patterns and the cost implications of each
• Sandbox providers: overview of the AI sandbox provider landscape