GPU explorer

LLM inference planning — compare GPU generations by memory, bandwidth, and cost efficiency

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💡 Top-right = high VRAM and throughput. These GPUs handle larger models and longer contexts.

Bubble size represents BF16 TFLOPs.

Throughput Index is a planning metric derived from memory bandwidth, VRAM, and architecture generation. It enables relative GPU comparison — not exact model throughput.

Inference performance depends on model architecture (GQA vs MHA), sequence length, batching, and inference backend (vLLM, TensorRT-LLM, etc.).

Hardware cost and cost efficiency axes appear when costings is enabled in Settings.