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 Groq
Pricing, pros, cons, and ideal use cases — side by side.
GroqFreemium
An inference provider whose custom LPU hardware delivers exceptionally low-latency responses for open-weight models.
At a glance
| Baseten | Groq | |
|---|---|---|
| Pricing | PaidUsage-based pricing tied to the compute your deployed models consume. | FreemiumFree tier for evaluation. Usage-based paid tiers for production volume. |
| 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 | Latency-sensitive applications like voice agentsReal-time and interactive AI experiencesTeams running supported open models |
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
Groq
Pros
- Exceptional inference speed and low latency
- OpenAI-compatible API, easy to adopt
- Strong fit for real-time use cases
- Competitive usage pricing
Cons
- Curated model selection, not every model
- Pure inference — no platform or governance layer
- Capacity can be constrained at peak demand
Which should you choose?
Groq 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; Groq leans more toward latency-sensitive applications like voice agents. Shortlist the one whose strengths line up with your biggest constraint.