Modal vs Baseten for inference

Both Modal and Baseten are platforms for AI model deployment. Modal's high-performance container technology makes it superior for real-time production inference. However, Baseten is a good choice if you need on-premise deployments.

Get Started

What is Modal?

Modal is a serverless platform that enables developers to run compute-intensive workloads in the cloud. Using a simple Python SDK, any Python function can be run in the cloud without managing or configuring infrastructure. Most common use cases include AI inference on GPUs, model fine-tuning, and batch data processing. Modal's proprietary Rust-based container stack is the fastest on the market for real-time AI applications. Try it out for yourself in the Modal Playground.

What is Baseten?

Baseten is an AI inference platform focused on deploying machine learning models as APIs. It offers both cloud and on-prem deployment options. Using Truss, an open-source model packaging framework, any model code and configuration can be containerized and deployed.

Performance and cold starts


Sub-second GPU container cold starts
Proprietary Rust-based container stack built for performance
Memory snapshotting for fast container imports
Ability to autoscale to thousands of GPUs in minutes
Templates for latency-optimized deployments of popular models
White-glove engineering support to optimize your AI workloads

Pricing


$30/mo in free compute credits
Usage-based pricing with no reservations or minimums
Granular per-second billing
Cheapest usage pricing for H100s, A100s, A10Gs, L4s, and T4s
Cheapest usage pricing for CPU instances
Volume discounts for enterprises
Transparent pricing for pro and team tiers

GPU options


B200
H100
A100 80GB
A100 40 GB
L40S
A10G
L4
T4
Instant access to all GPU types without quota requests

Security and enterprise readiness


Added security and container isolation with gVisor runtime
SOC 2 Type II
HIPAA
Dedicated model deployments
Run models in your VPC
Fine-grained observability down to individual inputs and containers

Additional capabililties


Persistent storage
Sandboxed code execution for agents
Parallelized batch data jobs
Compound AI systems
Offline inference
Model training
Model fine-tuning
Cron jobs

Developer experience


Attach GPUs and define custom images with one line of code
Python-defined infrastructure
No YAML or Dockerfiles needed
One-step creation of API endpoints for model deployments
Seamless integration between dev and prod environments
Hot reloading
Insanely fast image builds and model deployments for fast iteration

Choose Modal for:

Fast cold-starts

Autoscaling

Developer velocity and ease of use

Choose Baseten for:

Self-hosted inference

Fixed scale workloads