Topic: Hardware Optimization & Inference Engines
Explore our technical articles and implementation guides tagged with Hardware Optimization & Inference Engines.
Self-Hosting LLMs vs API Costs: Break-Even Math Guide
Comprehensive financial math guide for self-hosting LLMs versus using cloud APIs. Includes GPU TCO formulas, break-even token volume curves, and server energy cost analysis.
Optimizing KV Cache Utilization in vLLM Production Clusters
Production tutorial to optimize KV cache utilization in vLLM. Covers PagedAttention virtual memory mapping, memory fragmentation fixes, and prefix caching CLI configs.
NVIDIA Blackwell B200 vs Hopper H200 LLM Inference Analysis
Architectural benchmark comparison of NVIDIA Blackwell B200 vs Hopper H200 for LLM inference. Evaluates HBM3e memory bandwidth, FP4 FLOPS throughput, and TCO.
Best Local LLMs for 8GB VRAM Consumer GPUs: Hardware Benchmarks
Hardware benchmark guide evaluating the best open-weight local LLMs for 8GB VRAM consumer GPUs. Includes token-per-second decoding speeds, context spillover, and quantization metrics.
FP4 vs FP8 vs INT4 Quantization: Performance & Accuracy
Technical comparison guide analyzing FP4, FP8, and INT4 quantization formats. Evaluates micro-scaling formats, hardware acceleration across NVIDIA Hopper & Blackwell, and accuracy.
