Tooling
PrismML releases Bonsai 27B with 1-bit quantization for browser inference
PrismML's Bonsai 27B compresses a 27-billion-parameter model to 3.8GB using 1-bit quantization, enabling local inference directly in web browsers via custom WebGPU kernels.
1 min read
Sourcer/localllama
PrismML released Bonsai 27B, a 1-bit quantized version of a 27-billion-parameter dense language model designed to run locally in web browsers using custom WebGPU kernels. The model shrinks from 54GB to 3.8GB, a 93% reduction in model size, while retaining approximately 90% of the original model's pe...
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