GigaGPU Blog

GPU Hosting & AI Engineering Blog

Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.

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Benchmarks

Mistral 7B and Mistral Small 22B Benchmarks Across Every GPU We Host

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 catalogue, FP16, FP8 and AWQ-INT4.

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Latest Articles

Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.

Tutorials May 2026

How to Build a Production AI Inference Server: Hardware, Software, and the 8 Mistakes Everyone Makes

A practical, opinionated playbook for building a production-grade AI inference server — from picking the GPU to wiring up auth,…

Qwen 2.5 32B VRAM Requirements: FP16, FP8, INT4 and KV Cache Explained

Qwen 2.5 32B fits on a single 80 GB datacenter card or a 96 GB workstation card at FP16, but…

Self-Hosted Qwen 2.5 72B Deployment Guide: Hardware, vLLM Config, Real Benchmarks

A practical, end-to-end guide to deploying Qwen 2.5 72B on dedicated GPU hardware — from picking the right VRAM tier…

vLLM vs Ollama for Production Deployment: Decision Guide 2026

Side-by-side comparison of vLLM and Ollama for production LLM serving with throughput numbers, setup recipes, and a clear decision matrix.

RTX 5080 16GB vs RTX 3090 24GB: Compute or VRAM in 2026?

RTX 5080 16GB vs RTX 3090 24GB in 2026: FP4/FP8 throughput against raw VRAM. Hard numbers, per-model benchmarks and an…

GPU Cloud vs Dedicated Server: Which Wins in 2026?

Honest 2026 comparison of GPU cloud (AWS, RunPod, Vast) vs dedicated GPU servers. Real prices, hidden costs, break-even maths, and…

Flux.1 Deployment Guide: dev, schnell, and pro on Dedicated GPUs

Production deployment guide for Flux.1 dev, schnell and pro on dedicated GPUs - VRAM tables, throughput, ComfyUI/diffusers/Forge, quantisation, Docker recipe.