Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Head-to-head benchmark comparing LLaMA 3 70B and Mixtral 8x7B for text summarisation workloads on dedicated GPU servers, covering throughput, latency, VRAM usage, and cost efficiency.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Head-to-head benchmark comparing Mixtral 8x7B and Qwen 72B for function calling workloads on dedicated GPU servers, covering throughput, latency, VRAM…
Head-to-head benchmark comparing DeepSeek 7B and Gemma 2 9B for chatbot / conversational ai workloads on dedicated GPU servers, covering…
Head-to-head benchmark comparing CodeLlama and DeepSeek Coder for code-assist chatbot workloads on dedicated GPU servers, covering throughput, latency, VRAM usage,…
Head-to-head benchmark comparing SD 1.5 and SDXL for cost-optimised batch processing workloads on dedicated GPU servers, covering throughput, latency, VRAM…
Head-to-head benchmark comparing YOLOv8 and PaddleOCR for api serving (throughput) workloads on dedicated GPU servers, covering throughput, latency, VRAM usage,…
Head-to-head benchmark comparing YOLOv8 and PaddleOCR for document processing / rag workloads on dedicated GPU servers, covering throughput, latency, VRAM…
LLaMA 3 8B benchmarked on RTX 3090: 62 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
LLaMA 3 8B benchmarked on RTX 4060 Ti: 28 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment…
LLaMA 3 8B benchmarked on RTX 4060: 18 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
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