GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Pixtral 12B on a Dedicated GPU
Mistral's Pixtral 12B is a capable vision-language model with native variable image resolution - a practical generalist VLM for dedicated hosting.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Phi-3.5 MoE on a Dedicated GPU
Microsoft's Phi-3.5 MoE offers 42B total parameters with 6.6B active - strong quality with compute efficiency on a dedicated GPU.
ORPO vs DPO – Single-Stage vs Two-Stage Alignment
ORPO combines SFT and preference optimisation into one stage. DPO runs them separately. Here is when each approach wins.
OLMo 2 Self-Hosted – Fully Open Weights and Data
Allen AI's OLMo 2 is one of the few truly open LLMs - weights, training data, and training code all…
GigaGPU GPU Tier Ladder 2026 – Entry to Flagship
A clear climbing order across every GPU we offer, with the specific workload each tier solves before the next one…
Four-GPU Server Inference Architecture Patterns
Three ways to use four GPUs in one chassis, and why most teams over-invest in tensor parallel when data parallel…
Dual RTX 5090 Llama 3 70B Deployment – Tensor Parallel Setup
A walkthrough of standing up a production-grade Llama 3 70B inference server on two RTX 5090s with tensor parallelism.
Disk Offload vs CPU Offload for LLMs
NVMe offload versus RAM offload when a model cannot fit on the GPU. Both are slow. One is worse.
Data Parallel vs Tensor Parallel in vLLM
When to run two vLLM instances versus one vLLM instance split across two GPUs - the decision framework.
CPU-GPU Offload Strategy for 70B Models
When VRAM is tight, CPU offload lets you run models that would not otherwise fit. The cost is speed -…
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