Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Phi-3 Mini benchmarked on RTX 5080: 82 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Mixtral 8x7B benchmarked on RTX 5080: 32 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
Mixtral 8x7B benchmarked on RTX 3090: 18 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
LLaMA 3 70B benchmarked on RTX 5090: 12.8 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and…
LLaMA 3 70B benchmarked on RTX 3090: 5.2 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and…
Gemma 2 9B benchmarked on RTX 5090: 112.3 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
Gemma 2 9B benchmarked on RTX 5080: 48.8 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and…
Mixtral 8x7B benchmarked on RTX 5090: 45 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
Stable Diffusion XL benchmarked on RTX 3090: 3.2 it/s, 6.4 images/min at 1024x1024, VRAM usage, and cost per 1K images.
Stable Diffusion XL benchmarked on RTX 4060 Ti: 1.9 it/s, 3.8 images/min at 1024x1024, VRAM usage, and cost per 1K…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
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