Comparison

Everstack vs Modal

These two overlap less than the search results suggest. Modal is general serverless compute with first-class GPUs, and it is very good at that. Everstack is AI infrastructure where sandboxed execution is one layer. If you need GPUs, use Modal. If you need agent code to run inside your own boundary next to the gateway that produced it, that is a different question.

EverstackEverstack
vs
ModalModal
View pricingRead documentation

What is Modal?

Modal is a serverless cloud platform for running Python workloads, with first-class GPU support and per-second billing. Starter is $0 plus compute with $30 monthly credits, Team is $250 plus compute, and Enterprise is custom. Its pricing page describes no self-hosting or on-premises deployment option.

Why teams choose Everstack

  • Runs on infrastructure you control, inside your own compliance boundary
  • Sandbox execution shares a trace with the model call that produced the code
  • Gateway, agent runtime and evaluations included rather than assembled

Modal: Strengths & Limitations

Strengths

  • Serverless compute done extremely well. Modal's cold start and scaling engineering is genuinely impressive and hard to replicate.
  • First-class GPU access with published per-second rates, from Nvidia T4 at $0.000164 per second to B300 at $0.001972. Everstack does not offer managed GPUs at all.
  • A Python-native developer experience that many teams find more pleasant than container orchestration.
  • Generous free credits: $30 a month on Starter, $100 a month on Team.
  • Volumes at $0.09 per GiB per month with 1 TiB free, which is a lot of included storage.
  • Genuinely strong network controls on Sandboxes: block_network=True drops all outbound traffic, outbound_cidr_allowlist restricts egress by CIDR, and Modal states that Sandboxes are not authorized to access other resources in your Modal workspace.

Limitations

  • Modal is a cloud platform. Its pricing page describes no self-hosting or on-premises option.
  • Team is $250 per month plus compute, so the platform fee arrives before any usage.
  • It is compute, not AI infrastructure. Model routing, agent state, memory, evaluations and observability over LLM calls are separate systems.
  • Correlating a sandbox execution with the model call that generated the code is a join you build and maintain yourself.

Everstack advantage

Self-hosted execution inside your boundaryOne trace across model call and executionNo platform fee before usageGateway and evaluations included

The facts, side by side

Licence, deployment model and list price, taken from each vendor's own documentation. Every source is linked at the bottom of this page.

FactEverstackModal
Deployment modelSelf-hosted with Docker, Firecracker or Kubernetes, or Everstack Cloud.Cloud only. Modal's pricing page describes no self-hosting or on-premises deployment.
Platform feeStarter $0, Build $20/month, Scale $100/month, Enterprise custom (August 2026).Starter $0 plus compute with $30 a month in free credits, Team $250 plus compute with $100 a month in credits, Enterprise custom (August 2026).
Compute pricingMetered sandbox compute by plan.Sandboxes and Notebooks bill CPU at $0.00003942 per core per second and memory at $0.00000667 per GiB per second. Standard Modal compute is cheaper at $0.0000131 and $0.00000222, so the sandbox rate is roughly three times it, and the sandbox rate is the one that applies here. A core means a physical core, about 2 vCPU, with a 0.125 core minimum. Volumes $0.09 per GiB per month with 1 TiB free (August 2026).
Managed GPUsNot offered. Everstack does not provide managed GPU compute.Yes, with published per-second rates including Nvidia T4 at $0.000164, L4 at $0.000222 and B300 at $0.001972 per second (August 2026).
Isolation backendsDocker, Firecracker microVM and Kubernetes.gVisor. Modal states that compute jobs are containerized and virtualized using gVisor, the sandboxing technology developed at Google.
Sandbox lifetimeBounded by the session and the limits you configure.Five minutes by default, configurable up to 24 hours. Worth setting deliberately rather than discovering.
Sandbox network controlsPer-sandbox egress policy.block_network=True drops all outbound traffic, outbound_cidr_allowlist restricts egress by CIDR, and Sandboxes cannot reach other resources in your Modal workspace. A genuinely good set.
Model gatewayIncluded, OpenAI-compatible, multi-provider.Out of scope.
Agent runtime and evaluationsSame control plane, sharing one trace.Out of scope.
Operational burdenReal. You deploy and operate it.None, and Modal is very good at hiding it.

Tiers and per-second rates read from modal.com/pricing on 31 August 2026, and Sandbox isolation, lifetime and network behaviour from Modal's own Sandbox documentation. Modal prices Sandboxes and Notebooks above its standard compute, so the sandbox rate is the one quoted first here. GPU rates are a subset; Modal publishes a fuller table. Verify before you model costs.

Feature comparison

Direct capability comparison across key dimensions

FeatureEverstackModal
Execution
Sandboxed code execution
Managed GPU compute
Serverless autoscalingVia Kubernetes
Isolation primitiveFirecracker microVMgVisor
Deployment
Self-hosting
Runs inside your compliance boundary
Zero operational burden
Platform
Multi-provider model gateway
Stateful agent runtime
Vector memory
Evaluations and scoring
One trace across model call and execution
Commercial
No platform fee before usageTeam is $250/month

The same job, in both products

Working code rather than adjectives. Each snippet follows the quickstart published by the product it belongs to.

Run code in an isolated environment

Modal's model is decorated Python functions deployed to their cloud. Everstack's is a sandbox you create and execute inside. Both are pleasant; they are solving adjacent rather than identical problems.

Everstack

sandbox.ts
import Everstack from "@everstack/node";const client = new Everstack({ apiKey: process.env.EVERSTACK_API_KEY });const sandbox = await client.sandboxes.create({ template: "python" });const result = await sandbox.exec("python -c 'print(2 + 2)'");console.log(result.stdout);await sandbox.stop();

Modal

app.py
import modalapp = modal.App("example")@app.function()def add() -> int:    return 2 + 2@app.local_entrypoint()def main() -> None:    print(add.remote())

Key evaluation questions

What to ask when comparing Modal to Everstack

QuestionEverstackModal
Can execution run on my own infrastructure?Yes, that is the default.No self-hosting option is described on the pricing page.
Do I get managed GPUs?No. Everstack does not offer them.Yes, with published per-second rates.
Is there a platform fee before usage?Starter is $0.Starter is $0, Team is $250 per month plus compute.
Does it include a model gateway and evaluations?Yes, sharing one trace with execution.No, those are separate systems.

Feature-by-feature analysis

Where each product is genuinely stronger, row by row

Where execution happens

Everstack wins
Everstack

On infrastructure you control, inside your own compliance boundary.

Modal

On Modal's cloud. Their pricing page describes no self-hosting or on-premises option.

Why Everstack

If AI-generated code touches regulated data, where it executes is a compliance question rather than a preference.

GPU compute

Modal wins
Everstack

Not offered.

Modal

First-class, with published per-second rates across a wide GPU range.

Why Modal

This is not close. If you need GPUs, Modal is the answer and Everstack is not a substitute.

What surrounds the execution

Everstack wins
Everstack

The model gateway that produced the code, the agent that orchestrated it and the evaluation that scored it are all on one control plane and in one trace.

Modal

Compute. The AI infrastructure around it is yours to assemble.

Why Everstack

Debugging an agent that wrote bad code means seeing the prompt, the completion and the execution together, which is a join you maintain if they live in separate systems.

Operational burden and scaling

Modal wins
Everstack

Real, and you own the scaling.

Modal

None, with autoscaling and cold start work that is genuinely excellent engineering.

Why Modal

A significant advantage for Modal that an honest comparison should state rather than skip.

Moving from Modal to Everstack

These are adjacent products rather than substitutes, so a straight migration is often the wrong framing. Modal is general serverless compute with GPUs; Everstack is AI infrastructure where sandboxes are one layer. Many teams should run both.

  1. 1

    Separate GPU work from agent code execution

    If you use Modal for model inference or training on GPUs, keep it. Everstack does not offer managed GPUs and moving that work would be a downgrade.

  2. 2

    Move agent code execution only

    Sandboxed execution of AI-generated code is the part that benefits from sitting next to the gateway and the trace.

  3. 3

    Re-express functions as sandbox executions

    Modal's decorated function model does not map directly. Code that ran as a deployed function becomes code executed inside a sandbox, which is a different shape and needs rewriting.

  4. 4

    Compare cost on your real workload

    Modal's per-second rates are competitive and its scaling is excellent, but price the sandbox line specifically: Sandboxes and Notebooks bill at roughly three times Modal's standard compute rate. Self-hosting is not automatically cheaper once you count the infrastructure and the attention.

What breaks

  • Modal decorators, App objects and deployment semantics have no Everstack equivalent.
  • Anything using Modal GPUs cannot move, because Everstack does not offer them.
  • Modal Volumes and their mount semantics differ from Everstack sandbox storage.

What does not carry over

  • Deployed Modal apps and their scaling configuration.
  • Volume contents.
  • Modal execution history and logs.

Read this part first

When to choose Modal instead

Modal is excellent at what it does and for a lot of workloads it is not really competing with us. Pick Modal over Everstack when any of these is true.

  • You need GPUs. Everstack does not offer managed GPU compute at all, so this is not a close call.
  • You want general serverless compute rather than AI infrastructure. Modal runs any Python workload, not just agent code.
  • You do not want to operate infrastructure. Modal's scaling and cold start engineering is genuinely hard to replicate.
  • You like the decorated-function programming model. Many Python teams find it more pleasant than containers, and that is a real productivity argument.
  • You have no data residency constraint. If running compute on Modal's cloud is fine, self-hosting buys you complexity rather than capability.
  • Your volume storage needs are large. 1 TiB free at $0.09 per GiB per month afterwards is generous.

Frequently asked questions

Common questions about choosing between Everstack and Modal

Ready to get started?

See how Everstack compares to Modal for your specific use case.

View pricingRead docs

Sources & References

Modal pricingModal documentationEverstack licence (Apache-2.0)

Last reviewed: August 31, 2026. This comparison is for informational purposes and reflects our understanding of competitor capabilities based on publicly available documentation.

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