Gemma 4 QAT models show faster speeds, less VRAM use

A user on Reddit's r/LocalLLaMA shared benchmark results for Gemma 4 models, specifically comparing Quantization-Aware Training (QAT) versions against standard quantized models on an AMD 7900 XTX GPU. The tests indicated that Gemma 4 QAT models offer significant speed improvements and reduced VRAM usage without any discernible loss in output quality. For instance, the 12B QAT model was 45% faster and used 5.7GB less VRAM than its Q8_0 counterpart, while also improving constraint-following tasks. AI

IMPACT Quantization-aware training shows promise for improving local LLM performance and accessibility.

RANK_REASON User-conducted benchmark of an existing model family with a new training technique. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

• AMD 7900 XTX
• Gemma 4
• Quantization-Aware Training
• Qwen 3.6

• model release
• product

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