AI Hardware & Accelerators
The economics of AI compute — training and inference cost, GPU-cluster sizing, HBM bandwidth, token cost and accelerator ROI across NVIDIA, AMD, TPU and custom silicon.
Inference Cost Calculator
Estimate deployment costs for AI models across cloud, edge, and hybrid infrastructures with per-query, per-token, and per-hour pricing models. Integrates GPU/ASIC rental rates, network egress, storage, and scaling overhead for accurate inference TCO analysis.
Training Cost Calculator
Calculate AI model training expenses including GPU cluster rental, data transfer, checkpoint storage, and engineering time with distributed-training overhead modeling. Supports LLM, vision, and multimodal training with FLOPs-to-cost mapping and carbon-footprint estimation.
GPU Cluster Sizing
Determine optimal GPU cluster configurations for training and inference workloads with interconnect topology modeling, memory-bandwidth balancing, and fault-tolerance planning. Supports NVIDIA, AMD, and custom accelerator clusters with InfiniBand and NVLink network analysis.
Model Fit Checker
Verify whether AI models fit within hardware constraints including GPU HBM capacity, on-chip SRAM, and interconnect bandwidth with layer-wise memory profiling. Supports model parallelism, pipeline parallelism, and ZeRO optimization recommendations for large-model deployment.
HBM Bandwidth Calculator
Estimate memory bandwidth requirements for AI workloads with operation-type analysis, data-movement profiling, and roofline model integration. Calculates HBM generation selection, channel count, and clock-speed requirements to eliminate memory-bound bottlenecks.
AI Chip Comparator
Compare AI accelerators across performance, cost, power, and software-ecosystem metrics with normalized benchmarking for training and inference workloads. Supports NVIDIA, AMD, Intel, Google TPU, Amazon Trainium, and custom ASICs with TCO-per-FLOP analysis.
Token Cost Estimator
Calculate infrastructure costs per token generated for LLM serving with batch-size optimization, KV-cache management, and speculative decoding impact. Models pricing for API providers and self-hosted deployments with demand-spike handling and multi-model routing.
LLM Serving Calculator
Estimate resources required to serve large language models at scale including GPU count, memory allocation, and network bandwidth with concurrent-user modeling. Supports continuous batching, prefix caching, and multi-LoRA serving for production-grade LLM deployment.
Accelerator ROI Calculator
Analyze return on investment for AI hardware purchases with workload-mix modeling, utilization-rate optimization, and competitive-cloud-pricing comparison. Calculates payback period, NPV, and IRR for on-premise GPU/ASIC investments vs. cloud-rental alternatives.
Edge AI Cost Calculator
Estimate deployment costs for edge AI devices including NPU/TPU chip selection, BOM optimization, power-supply design, and thermal-management integration. Models unit economics for mass-production scales with OTA update infrastructure and lifecycle maintenance costs.
Explore the PPA trade-space early