Anyone seen benchmarks comparing Gemma 4 4-bit QAT vs. 8-bit standard quants?
A Reddit user asks for direct benchmarks comparing Gemma 4 4-bit QAT with standard 8-bit quants.
A r/LocalLLaMA user is looking for benchmarks comparing Gemma 4 4-bit QAT models, via Unsloth, against standard 8-bit non-QAT quantized models. They understand QAT is expected to preserve much of the BF16 baseline accuracy, but want hard numbers against traditional 8-bit PTQ. The post highlights scattered feedback but no clear head-to-head evaluation yet.
This r/LocalLLaMA post is not about releasing a new model or an official benchmark, but rather about a practical issue within the community: the author is looking to see if anyone has already compared the 4-bit QAT model of Gemma 4, especially the version obtained or used through Unsloth, directly compared to traditional 8-bit non-QAT quant models. The core issue is that QAT (Quantization-Aware Training) is generally considered to retain the accuracy of the original BF16 model better than general post-training quantization PTQ. Therefore, although 4-bit QAT has lower bit counts and theoretically saves more memory and inference resources, it may still approach high-precision models in terms of quality.
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