GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
RTX 3090 vs RTX 5090 for LLM Inference: Ampere vs Blackwell in 2026
Full head-to-head of the RTX 3090 24GB and RTX 5090 32GB for LLM inference: bandwidth, FP8, tokens per watt and price performance.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
ZFS vs ext4 on a GPU Server for Model Storage
ZFS offers snapshots, checksums, and compression. ext4 is the fast default. For model weight storage on a dedicated GPU, which…
Zero-Downtime Model Swap in Production
Upgrading your LLM version should not take your API offline. Here is the pattern for swapping models with zero downtime…
Pricing Your AI API Profitably
An AI API reselling your dedicated GPU capacity can charge meaningfully below OpenAI while retaining healthy margin. Practical pricing framework.
PixArt Sigma Deployment Guide
PixArt Sigma is a transformer-based diffusion model that renders 4K images natively with strong text fidelity. Self-hosting it on a…
Graph RAG Self-Hosted Deployment
Graph RAG builds an entity-relationship graph from your corpus and queries it with an LLM. Heavy indexing cost, strong results…
Gradient Checkpointing VRAM Savings
Gradient checkpointing trades ~25% training speed for ~60% VRAM savings. Often the single setting that decides whether your fine-tune runs.
Graceful Shutdown of vLLM in Production
Killing a vLLM process drops in-flight requests. Handling SIGTERM properly lets requests finish before the process exits.
Break-Even Calculator – SDXL Self-Hosted vs API
SDXL image generation APIs charge per image. A dedicated GPU has fixed cost regardless of volume. Here is the math…
Break-Even Analysis vs OpenAI API on an RTX 5090
How much monthly API spend justifies moving to a dedicated RTX 5090? A concrete calculation with 2026 pricing.
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