the future of local llm

I couldn’t get Diffusion Gemma to run on kaggle.

The apps don’t support dLLMs yet (vLLM does, but I couldnt).

But this is the future.

Imagine combining powerhouse offline models (like Gemma 4 26B)...

with TurboQuant compression (which cuts the size by more than half)...

with 6-bit quantization (which offers 92% accuracy with an 80% reduction in size)...

with MoE (Mixture of Experts, which drops it down to 4B active parameters focused on your specific topic)...

and with Diffusion, which generates text vectorially instead of token-by-token.

Next year, we’ll have 26B models or larger... running on 8GB of VRAM at over 100 tokens per second on budget friendly consumer GPUs.

The only thing missing is all of this to come together at once, but every single one of these technologies has already been used in separate models by Google itself.

some clever guys out there might even have found this in huggingface already. I'm not a pro like you guys.