Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Hosting a customer-facing chatbot on the RTX 5060 Ti 16 GB — model choice, throughput, p99 latency, and the traffic threshold where you should upgrade.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
How well does the RTX 5060 Ti 16 GB host a coding assistant for a small team? DeepSeek-Coder 6.7B, Continue.dev…
Speculative decoding pairs a small draft model with a larger target model to predict tokens ahead of time. On a…
The 5060 Ti 16 GB is great for small-LLM hosting and SDXL — until it isn't. Here are the four…
Vast.ai marketplace of community GPUs is great for hobby work and short experiments, but production deployments need predictability. Here are…
Qwen 2.5 32B fits on a single 80 GB datacenter card or a 96 GB workstation card at FP16, but…
Should you run your AI workload on serverless GPUs (Modal, Replicate, RunPod serverless) or rent a dedicated GPU server? Real…
Exactly how much GPU memory each Code Llama variant needs at FP16, FP8 and AWQ-INT4 — plus KV cache for…
How much VRAM does SDXL actually need? Numbers for FP16, FP8, INT8, with and without ControlNets, LoRAs and refiners. Plus…
Real tokens-per-second, time-to-first-token and cost-per-million-tokens numbers for Mistral 7B Instruct and Mistral Small 22B on every GPU in the GigaGPU…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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