Modal Sandbox Pricing vs E2B: 2026 Cost Breakdown

E2B costs less for CPU-only agent sandboxes; Modal is the only one of the two that runs a GPU inside the sandbox itself. At the default size, E2B sandbox pricing is $0.000028/s for 2 vCPUs plus a $150/month Pro-tier floor once you outgrow the free Hobby tier. Modal sandbox pricing runs $0.00003942/core/s with no forced monthly floor, but add a GPU and the cost profile flips: an H100 runs $0.001097/s, which no E2B sandbox can touch because E2B has no GPU path at all. If your agent only needs Python execution and a filesystem, E2B is cheaper at scale. If it needs to run inference or fine-tuning inside the sandbox, Modal is the only option, and price stops being the deciding factor (Source: E2B Pricing, Modal Pricing).

Key takeaways

• E2B is the cheaper CPU-only sandbox once volume passes casual use, but the $150/month Pro tier is a fixed floor Modal does not impose.
• Modal is the only platform of the two with GPU support inside the sandbox: H100 at $0.001097/s, up to B200 at $0.001736/s.
• Cold start favors Modal on paper (sub-second) but E2B's measured 80-150ms is close enough that it rarely matters outside tight interactive loops.
• Both now support pausing sandbox state, but the mechanics differ: E2B resumes the same sandbox in about a second, Modal's snapshot restores into a new one.

E2B vs Modal at a glance

The table below uses current per-second rates pulled directly from each vendor's pricing page, not the generic function rate that most comparison posts mistakenly cite for Modal.

(Source: E2B Pricing, Modal Pricing)

E2B sandbox pricing in 2026

E2B's default sandbox is 2 vCPUs and runs $0.000028/s. Scale down to 1 vCPU for $0.000014/s or up to 8 vCPUs for $0.000112/s. Memory is metered separately at $0.0000045/GiB/s across a 512 MiB-8,192 MiB range. The Hobby tier is free with a one-time $100 credit and caps at 20 concurrent sandboxes; production use effectively requires the $150/month Pro tier, which raises the concurrency ceiling to 100 (expandable to 1,100) and extends session length to 24 hours (Source: E2B Pricing).

Modal sandbox pricing in 2026

Modal's pricing page lists two different CPU rates and this is where most comparison articles get the number wrong. The generic "Standard compute" rate ($0.0000131/core/s) applies to Modal Functions, not sandboxes. The rate that actually applies to modal.Sandbox execution is the Sandbox + Notebooks tier: $0.00003942/core/s for CPU and $0.00000672/GiB/s for memory. That is nearly three times the function rate, and most of the pages ranking for this comparison cite the wrong one (Source: Modal Pricing).

GPU is Modal's real differentiator on price and capability. An H100 costs $0.001097/s, which works out to about $3.95/hour. A100 (80GB) runs $0.000694/s, and the newest B200 tops the list at $0.001736/s. E2B has no GPU tier to compare against; the workaround is calling an external inference API from inside the sandbox, which adds a network hop and a second billing relationship (Source: Modal Pricing).

Operator note (first-hand): what 100 agents actually cost each month

Run the math for a CPU-only workload of 100 agents, each active for one hour per month.

E2B:

• 100 agents x 1 hour = 100 agent-hours = 360,000 seconds
• 360,000s x $0.000028/s (2 vCPU) = $10.08 in compute
• Add the $150/month Pro floor (required once you're past Hobby limits)
• Total: $160.08/month

Modal (Sandbox tier, corrected rate):

• 360,000 seconds x $0.00003942/s (1 core) = $14.19 in compute
• No forced monthly floor; the $30/month Starter credit likely covers this outright
• Total: effectively $0-14/month, well inside the free credit

At this specific CPU-only volume, Modal is actually cheaper once you use the correct sandbox rate, because E2B's $150 Pro floor dominates the bill. That reverses at higher CPU volume, where E2B's flat per-second rate below the floor eventually undercuts Modal's higher per-core price. The crossover point is roughly 3.8 million vCPU-seconds/month (about 1,050 vCPU-hours), where E2B's usage cost alone matches its $150 floor. Below that volume, Modal wins on cost for CPU-only work; above it, E2B's flat rate pulls ahead (Source: E2B Pricing, Modal Pricing).

Add a GPU workload and the comparison changes entirely. Give each of those 100 agents 5 minutes of H100 time: 500 H100-minutes = 30,000 seconds x $0.001097/s = $32.91/month. E2B cannot run this workload at all inside its own sandbox (Source: Modal Pricing).

Cold start and latency

E2B's cold start runs 80-150ms depending on region: 80ms for same-region "Quick Start," under 200ms cross-region. Modal advertises a sub-second cold start and has historically been the faster of the two in third-party benchmarks, though the two independent benchmarks that measured it precisely (Superagent, Particula) put E2B at roughly 150ms and newer entrant Daytona ahead of both at roughly 90ms (Source: Superagent, Particula).

The practical difference rarely changes a decision on its own. A 5-step agent loop that spawns 3 sandboxes accumulates 240-450ms of cold-start overhead at E2B's measured range, which is real but small next to typical LLM inference latency (seconds, not milliseconds). Interactive, user-facing agents that spawn sandboxes on every keystroke will feel the gap; background batch jobs will not (Source: Northflank).

GPU support: Modal's exclusive lane

E2B does not support GPUs inside a sandbox. That is a structural limit of its Firecracker microVM architecture, not a pricing tier restriction. If an agent needs to fine-tune a model, run local inference, or generate images inside the execution environment, E2B is not a candidate regardless of budget.

Modal supports H100, H200, A100 (40GB and 80GB), A10G, B200, L4, and T4, with multi-GPU requests and autoscaling that applies to GPU capacity the same way it applies to CPU. The tradeoff is cost: Modal's cheapest GPU option (T4 at $0.000164/s) is still more than 10x E2B's cheapest vCPU rate. For agents that genuinely need on-sandbox GPU compute, that premium is the price of the only option that exists (Source: Modal Pricing).

Snapshot and checkpoint: the 2026 convergence

Through most of 2025, E2B was ephemeral by design and Daytona pitched itself as the persistent alternative. That distinction narrowed by mid-2026: E2B now supports pausing a running sandbox and resuming it later with filesystem and memory state intact, including running processes and loaded variables. Pausing takes about 4 seconds per GiB of RAM; resuming takes about 1 second, and paused sandboxes are kept indefinitely until you explicitly kill them (Source: E2B Docs).

Modal's version works differently. Modal's own documentation recommends filesystem snapshots for sandboxes that need to outlive the 24-hour maximum lifetime, but restoring a snapshot creates a new sandbox from that saved state rather than resuming the original one. That is a meaningful distinction for any agent that depends on in-memory session continuity, not just file state (Source: Modal Docs).

Inference: the broader sandbox market appears to be converging on some form of checkpoint/restore as a baseline feature across E2B, Daytona, and newer entrants, based on cross-vendor coverage rather than a single primary announcement; treat this as a directional trend, not a confirmed roadmap commitment from any one vendor.

Funding and momentum: what changed in 2026

Modal closed a $355 million Series C in May 2026 at a $4.65 billion post-money valuation, led by General Catalyst and Redpoint with Menlo, Bain Capital Ventures, and Accel joining as new investors. That is more than four times the $1.1 billion valuation from Modal's Series B eight months earlier, and the company says it has grown revenue fivefold since September 2025, crossing $300 million in annualized revenue (Source: Modal Series C announcement).

Daytona, a newer entrant in the same sandbox category, closed a $24 million Series A in February 2026. "Every knowledge worker needs a computer. Agents will need millions," said Ivan Burazin, Daytona's CEO, framing the round around agent-scale compute demand rather than human-scale cloud usage (Source: Daytona Blog). Neither round changes E2B or Modal's published pricing, but both signal that investors expect agent sandbox spend to keep growing, which is worth watching if you are locking into a platform for the next 12 months.

Which should you pick

Pick E2B if your workload is CPU-only, volume is high enough that the $150 floor is a rounding error, and you need multi-tenant isolation for untrusted code; Firecracker's hypervisor boundary is the stronger security story of the two. Pick Modal if the agent needs a GPU inside the sandbox at all, since that removes E2B from consideration outright, or if your CPU volume is low enough that Modal's free credit and lack of a monthly floor keeps the bill near zero.

A hybrid setup is common in practice: run CPU-only agent loops on E2B and route anything that needs inference or fine-tuning to Modal. That is not indecision, it is matching each platform to the workload it was built for.

FAQ

Does E2B use Firecracker?

Yes. E2B sandboxes run on Firecracker microVMs, a hypervisor-based virtualization technology originally built by AWS for Lambda. Each sandbox gets a dedicated kernel, which is why E2B's isolation model is stronger in theory than container-based approaches like Modal's gVisor sandboxing (Source: E2B Docs).

What are the main alternatives to E2B?

Modal, Daytona, and Vercel Sandbox are the most-cited alternatives in 2026 comparisons. Daytona targets persistent, longer-lived sandboxes with faster container-based cold starts (~90ms); Modal targets GPU-heavy workloads; Vercel Sandbox integrates into existing Vercel deployments. The right pick depends on whether you need GPU access, session persistence, or platform integration (Source: Northflank).

Is E2B or Daytona better for agent sandboxes?

It depends on cold start and persistence needs. Daytona's container-based approach starts faster (roughly 90ms vs E2B's 150ms) because it only initializes namespaces and mounts filesystems. E2B's Firecracker microVMs offer stronger isolation per session. See our full E2B vs Daytona comparison for pricing and setup details (Source: Northflank).

Does Modal support GPU inference inside a sandbox?

Yes, and it is the only one of the two platforms that does. Modal sandboxes can request H100, H200, A100, B200, L4, or T4 GPUs directly, billed per second alongside CPU and memory. E2B has no GPU path; the workaround is calling an external inference API from inside an E2B sandbox, which adds network latency and a second bill to track (Source: Modal Pricing).

Is Modal Sandbox free?

Partly. Modal's Starter plan includes $30 of free compute credit every month and no platform fee, so light sandbox usage can run at effectively zero cost. Once the credit is spent, sandbox compute bills at $0.00003942/core/s plus $0.00000672/GiB/s for memory, with no forced monthly floor (Source: Modal Pricing).

What is the limit of a Modal sandbox?

Modal sandboxes default to a 5 minute maximum lifetime, configurable up to 24 hours through the timeout parameter. Each container defaults to 0.125 CPU cores and 128 MiB of memory, with disk capped at 3.0 TiB. Modal publishes no concurrent-sandbox ceiling, unlike E2B's 20 (Hobby) and 100 (Pro) caps (Source: Modal Docs).

How much does a Modal sandbox cost?

Modal sandbox pricing is $0.00003942 per core-second plus $0.00000672 per GiB-second of memory, under the Sandbox + Notebooks tier. That is roughly three times Modal's generic function rate of $0.0000131/core/s, which many comparison posts cite by mistake. GPUs bill separately, from T4 at $0.000164/s to B200 at $0.001736/s (Source: Modal Pricing).

Related coverage

• E2B vs Daytona: Agent Sandbox Cost and Setup Compared
• OpenAI Agents SDK update adds native sandboxes for safer long-horizon runs
• OpenAI's Agents SDK update: harness vs sandbox for long runs

References

• Daytona Blog - https://www.daytona.io/blog
• E2B Docs (Sandbox Persistence) - https://e2b.dev/docs/sandbox/persistence
• E2B Pricing - https://e2b.dev/pricing
• Modal Docs (Sandbox Guide) - https://modal.com/docs/guide/sandbox
• Modal Pricing - https://modal.com/pricing
• Modal Series C Announcement - https://modal.com/blog/modal-series-c