Sold by: Modal
Deployed on AWS
Modal is a serverless compute platform for AI, ML, and data teams.
4.5
Overview
Modal is a serverless compute platform for AI, ML, and data teams. We make it easy for developers to run workloads like ML inference, fine-tuning, and batch data jobs in the cloud. Our custom infrastructure allows us to spin up GPU-enabled containers in as little as one second, helping you iterate fast and scale up to large production workloads. We scale resources up and down for you so you only ever pay for what you use.
For custom pricing options and private offer please contact here .
Please contact sales@modal.com to discuss pricing before purchasing Modal.
Highlights
- Autoscale to hundreds of GPUs and back down to zero in seconds, without managing and configuring boilerplate infra.
- Deploy Python functions to the cloud using infrastructure-as-code to define custom container images and hardware requirements.
- Pay as you go and only pay for the resource time you use.
Details
Sold by
Delivery method
Deployed on AWS
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Features and programs
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Enterprise Platform Fee | The Enterprise tier monthly platform fee covers access to the full enterprise feature set, including >50 GPU concurrency, region selection, a private support channel, SSO, HIPAA BAAs, and more. This is separate from the usage component of billing, which is described in detail below. Usage pricing can be discounted based on volume commits. | $1,000,000.00 |
Dimension | Description | Cost/unit |
|---|---|---|
Modal Add-ons | Add-ons | $0.01 |
Modal Usage | Usage | $0.01 |
Vendor refund policy
All fees are non-refundable and non-cancellable except as required by law.
Legal
Vendor terms and conditions
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Private Slack channel with the Modal team.
support@modal.com
support@modal.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
Top
10
In Serverless Workloads
Top
10
In High Performance Computing
Top
50
In High Performance Computing
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
GPU Container Provisioning
Spin up GPU-enabled containers in as little as one second with custom infrastructure for rapid iteration and scaling.
Autoscaling Capability
Automatically scale resources from zero to hundreds of GPUs and back down based on workload demands without manual infrastructure management.
Infrastructure as Code Deployment
Deploy Python functions to the cloud using infrastructure-as-code to define custom container images and hardware requirements.
Serverless Compute Architecture
Serverless compute platform that abstracts infrastructure management for ML inference, fine-tuning, and batch data processing workloads.
Pay-Per-Use Resource Billing
Resource-based billing model that charges only for the actual compute time consumed during workload execution.
Distributed Computing Runtime
Unified runtime that distributes Python code and AI libraries across thousands of CPUs, GPUs, or both, scaling from single machine to large clusters
Multi-Framework Support
Support for distributed execution of XGBoost, PyTorch, vLLM, and other AI libraries within a single platform
Infrastructure Deployment Flexibility
Deployment options including fully managed Anyscale-hosted experience, bring-your-own-cloud (BYOC) into customer VPC, VM-based infrastructure (EC2), and Kubernetes environments (AWS EKS and SageMaker HyperPod)
Enterprise Security Integration
Native integration with AWS security frameworks including AWS Identity and Access Management (IAM) with inherited access controls, policies, and governance standards
Workload Optimization and Resilience
Built-in head node resilience, intelligent autoscaling, advanced scheduling, GPU sharing capabilities, and safe rollout mechanisms to maximize resource utilization and prevent cost overruns
Workflow Orchestration Framework
Open-source Metaflow framework for designing and developing data science and ML/AI applications
Managed Kubernetes Infrastructure
Scalable, cost-optimized, fully managed Kubernetes cluster specifically tuned for data-intensive batch workloads and GPU-accelerated computing
High Availability Management
Enterprise-grade infrastructure with managed high availability for business-critical ML and data workloads
Data Isolation and Compliance
SOC2 compliant security architecture ensuring no data or code leaves the customer's account
GPU Compute Support
Native support for demanding GPU requirements of modern AI and machine learning workloads
Standard contract
No
Customer reviews
reviewer2855421
Low-friction compute has accelerated my prototyping and supports fast code evaluation runs
Reviewed on Jun 22, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Modal Labs is to accelerate my prototypes because I find it effective.
A specific example of a prototype I accelerated using Modal Labs is when I wanted to run evaluations for code generation models, so I used Modal Labs to deploy containers to run them on a specific environment.
How has it helped my organization?
Modal Labs has positively impacted my organization and my work because I don't think there is any other provider that lets me attach it as functions, and I think it fits my workflow more naturally.
What is most valuable?
The best features Modal Labs offers are how quick it is to provision containers and the fact that you can attach compute as functions.
The speed of provisioning containers and the attached compute function are valuable to me because it makes it efficient and fast to use.
What needs improvement?
Modal Labs could be improved by not charging for the building of containers, as it turns out to be more expensive for certain use cases like mine where I have to try out many different containers.
I chose an eight because if they made their free tier a bit more generous and also did not charge for building containers, I would give it a nine.
For how long have I used the solution?
I have been using Modal Labs on and off for around a year.
What other advice do I have?
I don't have anything else to add about my main use case or how Modal Labs fits into my workflow.
I don't want to add anything else about the features.
I don't measure my outcomes with Modal Labs, but my experience has been pretty good for use cases where other providers, which usually involve renting out the full VM, is too much of a high-friction option. This being low-friction is valuable.
I have no comments regarding Modal Labs's AI capabilities, specifically about its governance and security because I haven't used it in that context.
Regarding Modal Labs's AI capabilities, I find its accuracy and reliability of output to be extremely reliable. I don't think there is anything to improve regarding accuracy because it is a provider.
I use Modal Labs for experimentation on and off, and I do not properly deploy it.
I did not purchase Modal Labs through the AWS Marketplace . I used the free tier.
My advice to others looking into using Modal Labs is to try it, as they have thirty dollars of free credits every month.
I give Modal Labs an overall rating of eight.
Lovey P.
Effortless API Integration with Minimal Distractions
Reviewed on Apr 22, 2026
Review provided by G2
What do you like best about the product?
I really appreciate the main dashboard's layout in Modal Labs because it has the very bare minimums needed to get the job done without distractions from unnecessary decorative elements. I also like the eco-friendly dark theme. The initial setup of Modal Labs was very, very easy for me, which was a big plus.
What do you dislike about the product?
Most, if not all, interactive elements on the platform lack tooltips. Tooltips are essential, very much so.
What problems is the product solving and how is that benefiting you?
I use Modal Labs for running server-side scripts and serving Python ML API, enjoying its distraction-free dashboard layout.
Himanshu J.
Effortless Cloud Workloads with Minimal Setup
Reviewed on Apr 16, 2026
Review provided by G2
What do you like best about the product?
What I like most about Modal Labs is how simple it makes running cloud workloads without dealing with infrastructure directly. You can define functions and run them in the cloud with minimal setup, which feels very smooth compared to traditional cloud platforms.
What do you dislike about the product?
The main downside is that it requires some understanding of how serverless or cloud execution works. For beginners, it might not be immediately intuitive.
What problems is the product solving and how is that benefiting you?
Modal Labs solves the problem of setting up and managing cloud infrastructure for compute-heavy tasks. Instead of manually configuring servers or environments, you can just write code and run it directly.
This benefits me by saving time, reducing setup complexity and making it easier to experiment with workloads like data processing or AI tasks.
This benefits me by saving time, reducing setup complexity and making it easier to experiment with workloads like data processing or AI tasks.