In r/LocalLLaMA, Gemma 4 excitement centers on running capable local models with lower memory and strong speed, plus experimentation with quantization and llama cpp tooling for practical setups.
Gemma 4 26b is the perfect all around local model and I'm surprised how well it does.
I've been experimenting with TurboQuant KV cache quantization in llama.cpp (CPU + Metal) on Gemma 4 26B A4B-it Q4_K_M on an Apple M4 Pro 48GB, and the results look surprisingly strong.
Result size is 16GB and works the best IMO.
I’ve been experimenting with TurboQuant KV cache quantization in llama.cpp (CPU + Metal) on Gemma 4 26B A4B-it Q4_K_M on an Apple M4 Pro 48GB, and the results look surprisingly strong.
On Gemma 4, QJL seems to work well, and FWHT as a structured rotation substitute also looks like a good fit for the large attention head
I wanted to see how it performs against Qwen3.5 for local agentic coding.
I've been told qwen 3 coder next was the king, and while its good, the 4bit variant always put my system near the edge.
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