AI Infrastructure Cost Planner
Plan your AI infrastructure costs across GPU compute, model inference, training pipelines, and vector databases. Get monthly cost estimates for production-scale AI.
- Free Cost Planner
- GPU Pricing
- Multi-Cloud
AI Infrastructure Cost Planner
Frequently asked questions
How much does AI infrastructure cost?
Costs vary widely: a simple inference API might cost $500-2,000/month, while production AI with training, vector search, and observability typically runs $5,000-50,000/month. GPU costs dominate.
Should I use managed AI services or self-host?
Use managed services (OpenAI API, Bedrock, Vertex AI) for prototyping and moderate-scale inference. Self-host when you need full control, have compliance requirements, or when inference volume makes API costs prohibitive.
How do I reduce GPU costs?
Use model quantization (4-bit, 8-bit), implement request batching, leverage spot/preemptible GPUs for training, use smaller models where possible, and implement smart caching for repeated queries.
What vector database should I use?
Pinecone for fully managed simplicity, Weaviate or Qdrant for open-source flexibility, pgvector for PostgreSQL shops with moderate scale. Choice depends on scale, latency needs, and ops team capacity.
Need Help Planning AI Infrastructure?
We design AI platforms that scale to millions of requests while keeping costs predictable. Book a discovery call to plan your AI infrastructure.
Or email sales@perimattic.com