Answer 4 simple questions about your workload. Get GPU recommendations, VRAM requirements, cloud costs, and full TCO — instantly, no signup needed.
Want architecture recommendations, GPU sizing rationale, cloud vs on-prem analysis, and cost estimates?
The calculator estimates VRAM requirements based on model size, quantization strategy, context window, workload type, and concurrency. It then maps requirements to common NVIDIA GPU options and estimates cloud and on-prem costs.
Depending on precision and context length, Llama-class 70B models often require multi-GPU deployments or high-memory accelerators.
H100 generally offers significantly higher performance and memory bandwidth for modern AI workloads.
Total Cost of Ownership includes infrastructure, cloud spend, operations, maintenance, and utilization costs.
Built by Shantanu Goel, AI Product Manager focused on AI Infrastructure, Azure AI Factory, GPU sizing, AI economics, and enterprise AI adoption.
Consulting & Collaboration: shantanuiimu@gmail.com
Choose from LLM inference, fine-tuning, RAG pipelines, or embedding generation. Each workload has different VRAM and compute requirements.
Select model size (1B to 140B+ parameters), precision (FP16, INT8, QLoRA 4-bit), concurrent users, and context length up to 128K tokens.
Choose cloud, on-prem, or compare both. Specify latency requirements (real-time, interactive, batch) and deployment stage (prototype or production).
Instantly see ranked GPU options (H100, A100, L40S, T4), VRAM requirements, cloud cost per hour/month/year, on-prem purchase cost, and TCO breakeven.
AI Advisor covers the four most common enterprise AI infrastructure patterns. Whether you're running a 70B parameter model for real-time inference, fine-tuning a 7B model with QLoRA on medical records, building a RAG pipeline over millions of documents, or generating embeddings at scale — the sizing engine calculates exact VRAM requirements and recommends the right GPU from a database of 9 production-grade options.
Calculate GPU requirements for serving Llama 3.1, Mistral, Mixtral, and other open-source LLMs to concurrent users.
Estimate VRAM for full fine-tuning, LoRA adapters, and QLoRA 4-bit training across 1B to 70B+ parameter models.
Size retrieval-augmented generation systems including base LLM VRAM plus embedding model overhead for document retrieval.
Compare cloud GPU costs (H100, A100, T4) vs on-prem purchase price with breakeven analysis for your usage hours.
AI Advisor includes pricing and specifications for 9 production GPUs: NVIDIA H100 80GB SXM5 ($3.20/hr), H100 80GB PCIe ($2.60/hr), A100 80GB ($2.10/hr), A100 40GB ($1.60/hr), L40S 48GB ($1.40/hr), RTX 4090 24GB ($0.80/hr), A10G 24GB ($0.90/hr), T4 16GB ($0.35/hr), and V100 16GB ($0.55/hr). All pricing reflects typical cloud spot/on-demand rates.