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Gemma 3 QAT Models: Bringing AI to Consumer GPUs

(developers.googleblog.com)
602 points emrah | 3 comments | 20 Apr 25 12:22 UTC | HN request time: 0.595s | source
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holografix ◴[20 Apr 25 13:27 UTC] No.43743631[source]▶
Could 16gb vram be enough for the 27b QAT version?
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1. hskalin ◴[20 Apr 25 14:02 UTC] No.43743825[source]▶
With ollama you could offload a few layers to cpu if they don't fit in the VRAM. This will cost some performance ofcourse but it's much better than the alternative (everything on cpu)
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2. senko ◴[20 Apr 25 16:09 UTC] No.43744666[source]▶
I'm doing that with a 12GB card, ollama supports it out of the box.

For some reason, it only uses around 7GB of VRAM, probably due to how the layers are scheduled, maybe I could tweak something there, but didn't bother just for testing.

Obviously, perf depends on CPU, GPU and RAM, but on my machine (3060 + i5-13500) it's around 2 t/s.

3. dockerd ◴[21 Apr 25 14:22 UTC] No.43752342[source]▶
Does it work on LM Studio? Loading 27b-it-qat taking up more than 22GB on 24GB mac.