Sold by: Baseten
Deployed on AWS
Machine learning infrastructure that just works
4.3
Overview
At Baseten, we provide all the infrastructure you need to deploy and serve ML models performantly, scalably, and cost-efficiently.
With Baseten, you can:
- Deploy your proprietary ML models with optimized serving engines.
- Deploy open-source models on dedicated instances.
- Handle massive traffic spikes with autoscaling model deployments.
- Save on infra costs with scale to zero and lighting fast cold starts.
- Manage deployments, metrics, and spending with role-based access control.
Connect with us to discuss your ML infrastructure needs and learn more about our available live engineering support, custom POCs, volume discounts, and self-hosted options.
Highlights
- Highly performant autoscaling infrastructure that goes from prototype to production seamlessly.
- Reliable logging and visibility across deployments, health, metrics, and spend in your Baseten workspace.
- Enterprise-grade security and reliability with SOC 2 Type II, HIPAA compliance, and custom SLAs.
Details
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You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Trust Center
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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 |
|---|---|---|
Baseten Base Package | Listed pricing is indicative only. All purchases are completed via AWS Marketplace private offers tailored to your requirements. Reach out to request a custom quote and private offer | $100,000.00 |
Dimension | Description | Cost/unit |
|---|---|---|
additional_usage | Additional usage | $1.00 |
Dimensions summary
This listing uses a contract structure built around two dimensions. The Baseten Base Package covers your core committed spend, set through a private offer tailored to your needs. Additional usage bills separately for consumption beyond that base amount. You pay only for the compute your models actively use, billed by the minute, with no charge for idle time. All prices shown are indicative, and final terms come through a custom quote and private offer arranged with the vendor.
Top-of-mind questions for buyers
You pay only for the time your model actively uses compute, billed down to the minute. This covers deploying, scaling up or down, and making predictions. Idle time carries no charge. You control how your model scales up and down.
The Baseten Base Package covers your committed spend arranged through a private offer. Additional usage bills separately for consumption beyond that base amount. Both appear together, with the base as your floor and additional usage capturing overage. Your active compute time drives what accrues.
You can deploy open-source and custom models, or start from an off-the-shelf model library. Compute options include a range of GPU and CPU instance types, with control over which GPUs your models use. Reach out to the vendor to request additional GPU types or regions.
www.baseten.co
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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
Our standard email support is available Monday through Friday during business hours (Pacific time).
We offer substantial additional support options, including Slack connect, live engineering support, custom POCs, and custom response SLAs.
support@baseten.co
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
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
Model Deployment and Serving
Supports deployment of proprietary ML models with optimized serving engines and open-source models on dedicated instances.
Autoscaling Infrastructure
Handles massive traffic spikes with autoscaling model deployments and supports scale to zero functionality with fast cold starts.
Monitoring and Observability
Provides reliable logging and visibility across deployments, health metrics, and spending through a centralized workspace.
Access Control and Management
Includes role-based access control for managing deployments, metrics, and spending across the infrastructure.
Security and Compliance
Implements SOC 2 Type II certification, HIPAA compliance, and custom SLAs for enterprise-grade security and reliability.
GPU Container Provisioning
Custom infrastructure enables GPU-enabled container spin-up in approximately one second for rapid iteration and scaling.
Autoscaling Capability
Automatic scaling to hundreds of GPUs and down to zero resources within seconds without manual infrastructure configuration.
Infrastructure-as-Code Deployment
Python functions deployable to cloud using infrastructure-as-code approach with custom container image and hardware requirement definitions.
Resource Optimization
Dynamic resource allocation that scales up and down based on workload demands to optimize resource utilization.
Serverless Compute Architecture
Serverless platform supporting ML inference, fine-tuning, and batch data job execution without infrastructure management overhead.
Model Deployment Infrastructure
Inference Endpoints enable deployment of machine learning models as secure, production-ready APIs with fast inference capabilities.
Application Hosting Platform
Spaces provides hosting infrastructure for machine learning applications with integrated GPU resources and pre-configured dependencies.
Enterprise Access Control
Enterprise Hub includes Single Sign-On, Resource Groups, and Audit Logs for advanced security and access management.
Model and Dataset Repository
Platform hosts over 1 million pre-trained models, datasets, and AI applications for text, image, audio, and video processing tasks.
Standard contract
Customer reviews
Ashkan K.
Effortless AI Model Deployment and Scaling with Fast Inference and Great Tooling
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
What I like best about Baseten is how easy it makes deploying and scaling AI models in production. The combination of fast inference, autoscaling, and good developer tooling means I can focus more on the model and application rather than managing GPU infrastructure. I also like the flexibility to deploy custom or fine-tuned models while still getting strong performance and observability.
What do you dislike about the product?
What I dislike about Baseten is that it can take a while to get comfortable with the platform, particularly when you’re setting up more advanced deployments. Pricing can also be hard to predict if your workloads have variable usage, and some features can feel better suited to teams with strong technical expertise.
What problems is the product solving and how is that benefiting you?
Baseten helps cut through the complexity of deploying, scaling, and managing AI models in production. It reduces the time I have to spend on infrastructure work, GPU resources, and performance optimization. As a result, I can get AI applications into production faster, keep performance more reliable over time, and focus more on improving the product itself instead of managing the underlying infrastructure.
Recommendations to others considering the product:
To improve Baseten, I would suggest enhancing the onboarding process to make it more intuitive for new users. Additionally, providing clearer pricing models and offering more resources for users with varying levels of technical expertise could be beneficial.
Ganesh R.
A straightforward way to deploy and test AI models
Reviewed on Aug 25, 2026
Review provided by G2
What do you like best about the product?
What I like most about Baseten is that it makes deploying AI models feel much simpler. I like being able to get a model running behind an API without having to deal with all the infrastructure myself. The deployment workflow is fairly straightforward, and the autoscaling and inference setup make it useful for quickly testing an idea and seeing how it could work in production.
What do you dislike about the product?
The basic workflow is pretty easy to understand, but some of the more advanced deployment and scaling options take a bit of time to figure out. I also think the pricing and resource usage could be easier to understand when you're experimenting with different models.
What problems is the product solving and how is that benefiting you?
Baseten takes away a lot of the infrastructure work involved in deploying and serving AI models. Instead of setting up GPU infrastructure, model serving, scaling, and APIs separately, I can use one platform to handle most of that. For me, the main benefit is being able to spend more time testing models and building the application instead of worrying about the deployment side.
David H.
Baseten Makes ML Model Deployment Fast, Simple, and Reliable
Reviewed on Aug 20, 2026
Review provided by G2
What do you like best about the product?
Deploying machine learning models becomes easy using Baseten. One of the greatest strengths of the platform is that you do not need any complicated infrastructure to deploy the model as an API. The user-friendly documentation, fast development cycle, and support from the team contribute to efficient model deployment. Automatic scaling helps to maintain reliability during high traffic periods.
What do you dislike about the product?
There are still some areas where Baseten can improve its enterprise capabilities. More sophisticated monitoring, more compliance certifications, and better role-based access control would be appreciated. The integration scope of third-party products is narrower than that of other machine learning platforms due to the lightweight architecture of Baseten, and the tuning options for big datasets are not as numerous as for heavyweights such as SageMaker.
What problems is the product solving and how is that benefiting you?
Baseten takes away the burden of server management involved in deploying an ML model and allows for greater emphasis to be put on building a more effective model. This enables rapid time to market since prototypes can be put into production within hours rather than weeks. Baseten automatically scales, saving time and money.
Muhammad O.
Reliable Platform for Fast AI Model Deployment
Reviewed on Aug 05, 2026
Review provided by G2
What do you like best about the product?
What I like most about Baseten is how quickly it lets me deploy and test AI models without having to deal with complicated infrastructure. The interface feels clean and easy to navigate, the API integration is straightforward, and performance has been consistent for my inference workloads. Overall, it makes experimenting with different models faster, smoother, and more efficient.
What do you dislike about the product?
What I dislike most is that some of the more advanced deployment settings and configuration options come with a steep learning curve for new users. The documentation is solid overall, but I’d really appreciate more beginner-focused tutorials, more real-world examples, and clearer step-by-step guidance for first-time deployments so it’s easier to get started with confidence.
What problems is the product solving and how is that benefiting you?
Baseten helps us deploy and serve AI models much faster, without having to spend time managing infrastructure. It streamlines model hosting, scaling, and API deployment, so our team can stay focused on building and testing AI applications rather than maintaining backend systems. As a result, our deployment process takes less time and our overall development efficiency has improved.