Gemma 4 QAT models spark debate over performance and utility
ByPulseAugur Editorial·[14 sources]·
Users are discussing the performance and utility of Gemma 4QAT (Quantization Aware Training) models, particularly comparing them to standard quantizations. While some users report improved speed and quality for general tasks, others find QAT models to be a regression, especially for specific use cases like tool calling or coding. Benchmarks are being conducted to quantify the differences, with mixed results suggesting that QAT models may not always outperform higher-bit standard quantizations and can sometimes exhibit unexpected behavior.
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User experiences and benchmarks provide insights into the practical performance of quantized models, influencing future model development and user adoption strategies.
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The cluster consists of user discussions and benchmarks comparing different quantizations of the Gemma 4 model, which falls under research and user experience analysis rather than a primary model release.
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Research
The cluster consists of user discussions and benchmarks comparing different quantizations of the Gemma 4 model, which falls under research and user experience analysis rather than a primary model r…
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14 independent sources
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model release, product
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High
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148 days old
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<p>Quantization-Aware Training (QAT) is the headline feature of the Gemma 4 release: models <em>trained</em> to survive 4-bit quantization, so the Q4 version stays close to full quality instead of degrading the way a naive post-training quant does. The pitch is great. I wanted to…
<!-- SC_OFF --><div class="md"><p>I have enough RAM+VRAM to use gemma4 26b a4b up to q6_k quantizations w/ decent performance. Does anyone have any comparisons of the Q4_0 QATs (at 4-bits/wt) vs non-QATs at >4 bits/wt? (ex: q6_K)?</p> <p>KLD vs the originals wouldn't be approp…
<!-- SC_OFF --><div class="md"><p>I'm trying to find out if anyone has done any benchmarking comparing the Gemma 4 4-bit QAT models (via Unsloth) against standard 8-bit non-QAT quants.</p> <p>I know QAT is supposed to retain a ton of accuracy compared to the baseline BF16, but I'…
<!-- SC_OFF --><div class="md"><p>Hopefully this isn't too low effort of a post. I just finished the benchmarks and I figured I'd post them online because they certainly were insightful for me. I did not use any AI other than asking Gemini 3.1 Pro if it was statistically signific…
<!-- SC_OFF --><div class="md"><p>I spent the last few days trying to get consistent tool calling out of the new Gemma 4 12b QAT model and had to give up. When the model actually works, it works great, but for my specific use case and workflows it is just not for me. It is a majo…
<!-- SC_OFF --><div class="md"><p>Hey everyone!</p> <p>Not a native speaker, so please correct my english where I make mistakes, (can only learn from it!).</p> <p>While it's been out only for just a while, I wanted to post about it because it's been such a joy.</p> <p>So, to say …
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1tzib7d/qat_variant_of_gemma4_26b_a4b_is_not_working_well/"> <img alt="QAT variant of Gemma4 26B A4B is not working well for me" src="https://preview.redd.it/albcm4kp0w5h1.png?width=140&height=140&crop…
<!-- SC_OFF --><div class="md"><p>I just came across the following post, where a user found some confusing divergence results between Q4 quants of the original and QAT models with a Q8/unquantized reference of the original model.</p> <p><a href="https://www.reddit.com/r/LocalLLaM…
<!-- SC_OFF --><div class="md"><p>No numbers. Not sure if anybody cares…</p> <p>I’ve run the UD version of Q4_k_m for a month. I talk to this model nicely, because it’s a functional nervous wreck. And initially I thought that might be an alignment thing, so I also have the hereti…
