Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Prompt caching trades VRAM for throughput. The economics depend on cache hit rate and traffic shape. Here is the math.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
AnimateDiff turns Stable Diffusion into a video model via motion modules. Setup, hardware sizing, and the workflows that work on…
How many documents per hour can each GPU summarise? Real numbers across the catalogue for typical map-reduce summarisation workloads.
ElevenLabs has the best closed-source TTS. Coqui XTTS v2 is the closest open-source alternative. Quality, latency, cost, and feature deltas.
How to budget for an AI deployment year-on-year — pilot phase, production phase, scale phase. With realistic numbers per team…
Docker is convenient. For GPU AI workloads it sometimes leaves performance on the table. Here is when bare-metal wins and…
How to architect a customer-support chatbot on dedicated GPU infrastructure — RAG over support docs, ticket-aware context, escalation logic, and…
Architecting a sub-1-second voice agent on dedicated GPU hardware — VAD, streaming Whisper, LLM with prefix caching, streaming TTS.
Four leading open-weight TTS models compared on quality, speed, voice cloning, and VRAM. Which one for which voice agent.
OpenAI Whisper Large-v3-Turbo is a 4x faster distilled variant. Quality, speed, language coverage compared with the full Large-v3.
Find exactly what you need — from GPU benchmarks to deployment tutorials.
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