BasetenPaid
A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.
AI Infrastructure comparison
Baseten vs LiteLLM
Pricing, pros, cons, and ideal use cases — side by side.
LiteLLMFreemium
An open-source LLM gateway that gives you one consistent API and proxy across 100+ model providers, with key management and spend tracking.
At a glance
| Baseten | LiteLLM | |
|---|---|---|
| Pricing | PaidUsage-based pricing tied to the compute your deployed models consume. | FreemiumOpen-source and free to self-host. A paid enterprise edition adds SSO, audit logs, and support. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Teams deploying custom or fine-tuned modelsEnterprises needing dedicated, autoscaling model servingOrgs that want to avoid managing GPU infrastructure | Teams using multiple model providersPlatform teams centralizing LLM access and spendEnterprises wanting provider portability |
Pros & cons
Baseten
Pros
- Production model serving without managing GPUs
- Autoscaling with fast cold starts
- Works with open, fine-tuned, and custom models
- Removes most MLOps overhead
Cons
- Unnecessary if you only use hosted frontier APIs
- Compute-based cost grows with traffic
- Still requires model and evaluation expertise
LiteLLM
Pros
- One consistent API across 100+ providers
- Proxy adds key management, budgets, and spend logging
- Avoids provider lock-in
- Lightweight to adopt
Cons
- Self-hosting the proxy is your operational burden
- A gateway is one more hop to monitor
- Advanced governance features are in the paid edition
Which should you choose?
LiteLLM is the lighter-weight option (Freemium), while Baseten sits higher on the pricing ladder (Paid). Baseten is built around teams deploying custom or fine-tuned models; LiteLLM leans more toward teams using multiple model providers. Shortlist the one whose strengths line up with your biggest constraint.