GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
RTX 5060 Ti vs 5060 Blackwell – The VRAM Choice
Both are Blackwell 5060 family. The 8GB vs 16GB decision shapes which models you can run, which concurrency you can sustain, and how production-ready your card is.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
RTX 5060 Ti 16GB with Chunked Prefill
Chunked prefill on Blackwell 16GB - how batching prefill and decode together smooths tail latency under concurrency.
RTX 5060 Ti 16GB Whisper Benchmark
Whisper large-v3 and Turbo transcription on Blackwell 16GB - measured real-time factors, VRAM, and batched WER trade-offs.
RTX 5060 Ti 16GB vs Repurposed RTX A5000
Used RTX A5000s circulate cheaply with 24GB ECC VRAM. Is the new mid-tier Blackwell really better than that second-hand deal…
RTX 5060 Ti 16GB vs RTX 5090 – The Downgrade Math
Many teams provisioned a 5090 when a 5060 Ti would serve their workload at 60% less monthly cost. How to…
Fine-Tuning an Embedding Model on a Dedicated GPU
Fine-tuning a small embedding model on your own query-document pairs almost always beats the off-the-shelf model for domain retrieval.
DPO Training on a Dedicated GPU Server
Direct Preference Optimisation aligns a model to preferred responses without reward model complexity. Here is the practical setup.
DeepSeek V3 Distilled Models – Self-Hosted Options
The distilled variants of DeepSeek V3 (and R1) fit on single GPUs and carry most of the reasoning quality -…
DeepSeek R1 Distill Qwen 32B Deployment
The distilled R1 in Qwen 32B is the practical reasoning model for dedicated GPU hosting. Here is the full deployment…
DeepSeek Coder V2 VRAM Requirements
DeepSeek Coder V2 comes in a 16B MoE variant and a 236B MoE variant. The VRAM story differs dramatically between…
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