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.
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.
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.
• Fast cold-starts • Autoscaling • Developer velocity and ease of use
• Self-hosted inference • Fixed scale workloads
Feature |  |  |
|---|---|---|
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 | | |
Feature | | |
|---|---|---|
$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 | | |
Feature | | |
|---|---|---|
B200 | | |
H100 | | |
A100 80GB | | |
A100 40 GB | | |
L40S | | |
A10G | | |
L4 | | |
T4 | | |
Instant access to all GPU types without quota requests | | |
Feature | | |
|---|---|---|
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 | | |
Feature | | |
|---|---|---|
Persistent storage | | |
Sandboxed code execution for agents | | |
Parallelized batch data jobs | | |
Compound AI systems | | |
Offline inference | | |
Model training | | |
Model fine-tuning | | |
Cron jobs | | |
Feature | | |
|---|---|---|
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 | | |