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Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Silero VAD Production Deployment
Voice activity detection separates speech from silence before transcription. Silero VAD is tiny, fast, and essential for streaming audio pipelines.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Sentence Transformers GPU Batch Tuning
sentence-transformers defaults to tiny batches. On a dedicated GPU, bigger batches deliver 5-10x throughput - and the right number depends…
Load Balancer in Front of vLLM – Patterns That Work
Two vLLM replicas need a load balancer. Picking the right algorithm and the right tool prevents uneven load, broken streaming,…
Late Interaction Retrieval – Self-Hosted Options
ColBERT, SPLADE, and hybrid approaches offer retrieval accuracy beyond single-vector search - a comparison of what actually runs in production.
LangGraph Production Deployment
LangGraph models agent workflows as state machines with explicit transitions. Production-grade on a self-hosted LLM takes a specific setup.
Contextual Retrieval Pipeline on a Dedicated GPU
Prepend each chunk with an LLM-generated context summary at index time. Recall improvements dwarf the index-time GPU cost.
Consulting Margins on AI Services Using a Dedicated GPU
AI consultants running client projects on a shared dedicated GPU can maintain 70%+ margins. Here's how the economics work.
ColBERT v2 on a GPU Server – Late Interaction Retrieval
ColBERT stores a vector per token rather than per document - late-interaction scoring that beats single-vector embeddings on many tasks.
vLLM on ROCm: Setup Guide for AMD GPUs (MI300X, RX 7900 XTX)
End-to-end guide to running vLLM on AMD ROCm GPUs, with install steps, model compatibility and CUDA performance comparisons.
SDXL for Ecommerce Product Images: GPU Sizing, LoRAs and Cost vs Midjourney
A practical guide to using SDXL for ecommerce product photography: batch throughput, LoRA workflows, ControlNet and cost per image versus…
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