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Benchmarking Self-Hosted Gemma 2 9B vs. Frontier APIs: The FP8 Quantization Prefill Tax and VRAM Realities on an NVIDIA L4 [P]

Reddit r/MachineLearning · 2026-06-27

This benchmark compares an unquantized Gemma 2 9B model with an FP8 quantized variant on an NVIDIA L4 GPU, revealing that FP8 quantization introduces a prefill tax (higher TTFT) but improves decoding latency and VRAM usage, with minimal semantic drift for narrow tasks.

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