Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
BF16 is the right default on modern GPUs. FP16 is legacy. The difference matters for numerical stability in LLM training.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
MeloTTS is a compact multilingual TTS that runs fast on almost any GPU - good voice quality and permissive licence.
Model Context Protocol lets any compatible client wire tools and resources into an LLM. Self-hosted MCP servers stay private on…
Fish Speech is a zero-shot voice cloning TTS that clones a voice from 10-30 seconds of reference audio. Runs on…
The FCA treats AI as another tool under existing rules. For fintech AI on dedicated hosting, the expectations are familiar…
Real embedding throughput per second for BGE-M3 and BGE-large across every GPU we host, measured under TEI with tuned batch…
When embedding quality matters more than cost, a 7B LLM-based embedder delivers substantially better retrieval than smaller dedicated embedders.
ZeRO-2 and ZeRO-3 let you train models that would not fit on a single GPU by sharding optimiser state and…
Nvidia DCGM Exporter emits Prometheus-format GPU metrics. Running it on a dedicated server is the right way to observe GPU…
The RTX 5060 Ti 16GB lands on GigaGPU - Blackwell silicon, 16GB of GDDR7 at 448 GB/s, native FP8 tensor…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
AI Hosting & Infrastructure
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