Gemma 4 Quantization-Aware Training (QAT) weights are now available on Ollama!
They reduce memory requirements while maintaining model quality.
E2B:
ollama run gemma4:e2b-it-qat
E4B:
ollama run gemma4:e4b-it-qat
12B:
ollama run gemma4:12b-it-qat
26B:
ollama run gemma4:26b-a4b-it-qat
31B:
ollama run gemma4:31b-it-qat
Try them with ollama launch integrations to use with your favorite tools 👇👇👇
We just dropped Gemma 4 Quantization-Aware Training (QAT) checkpoints on Hugging Face!
All Gemma 4 model sizes and their drafters are now optimized with QAT to cut memory requirements and maximize on-device performance!
Dear GitHub Copilot team,
I am happy to announce that I successfully burned all of my monthly tokens in under 3 days thanks to your garbage new pricing model.
I'd also like to inform you that I won't be renewing my subscription or adding more budget.
Best,
A former customer.
@witcheer The price of ‘freedom’ an investment of 3000+$ and monthly electricity bill 50-60$ to keep this machine alive 24/7 to run an open weight model? Does anyone see this? I know there are many advantages but there’s no break even point compared to cloud providers!
Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
@AishwaryaDevv I’ve just dropped Hermes and OpenClaw was about to do it… If you need a coding harness used Codex/Claude Code period, if you want a personal assistant cool and fancy then fight against the two first
@petergyang I’m more lean towards OpenClaw the level of effort from devs will come back with stability and reliability soon \ In the long run OC will lead
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