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The 30B Raspberry Pi Breakthrough That Flips GPU Optimization on Its Head

Recent advances in quantization and kernel optimization are enabling 30B-parameter models to run on Raspberry Pi devices, but the real story is how they expose a fundamental flaw in our understanding of model compression: fewer bits doesn’t always mean faster inference.

#kernel-optimization#llama.cpp#quantization...

GLM-4.7

Unsloth’s 2-Bit Miracle: How GLM-4.7 Lost 266GB Without Losing Its Mind

Unsloth’s aggressive 2-bit quantization slashes GLM-4.7 from 400GB to 134GB, forcing a reckoning with what ‘good enough’ means for frontier models

#GLM-4.7#local AI#model compression...

LLM

The Broken Promise of Quantization: Why Your 8GB Laptop Can’t Handle Real LLM Work

Testing reveals quantization thresholds where LLM capabilities degrade, exposing which tasks survive compression and which fail miserably.

#LLM#local-ai#quantization

fp8

The FP8 Revolution: How Unsloth Just Democratized Reinforcement Learning

Unsloth and TorchAO bring FP8 reinforcement learning to consumer GPUs, cutting VRAM needs by 60% while delivering 1.4x speedups. Can your local hardware really train competitive reasoning models now?

#fp8#gpu-optimization#local-training...