#startups #PrismML #Qualcomm
Website: prismml.com
Blog: prismml.com/news/bonsai-8b
HuggingFace: huggingface.co/collections/...
Website: prismml.com
Blog: prismml.com/news/bonsai-8b
HuggingFace: huggingface.co/collections/...
prismml.com/news/bonsai-...
x.com/PrismML/stat...
5.9gb compressed version of Qwen 3.8 27b while retaining 98.2% of aggregate benchmark performance
prismml.com/news/bonsai-...
x.com/PrismML/stat...
5.9gb compressed version of Qwen 3.8 27b while retaining 98.2% of aggregate benchmark performance
Whitepaper: github.com/PrismML-Eng/...
Models: huggingface.co/collections/...
WebGPU Demo: huggingface.co/spaces/webml...
GitHub: github.com/PrismML-Eng/...
Docs: docs.prismml.com
Whitepaper: github.com/PrismML-Eng/...
Models: huggingface.co/collections/...
WebGPU Demo: huggingface.co/spaces/webml...
GitHub: github.com/PrismML-Eng/...
Docs: docs.prismml.com
github.com/PrismML-Eng/...
github.com/PrismML-Eng/...
Whitepaper: github.com/PrismML-Eng/...
Models: huggingface.co/collections/...
HuggingFace Demo: huggingface.co/spaces/webml...
GitHub: github.com/PrismML-Eng/...
Whitepaper: github.com/PrismML-Eng/...
Models: huggingface.co/collections/...
HuggingFace Demo: huggingface.co/spaces/webml...
GitHub: github.com/PrismML-Eng/...
後で試す
PrismML-Eng/Bonsai-demo: Bonsai Demo https://github.com/PrismML-Eng/Bonsai-demo
後で試す
PrismML-Eng/Bonsai-demo: Bonsai Demo https://github.com/PrismML-Eng/Bonsai-demo
Более масштабная цель Prism — это открытый ИИ, который работает на устройствах и более эффективно использует уже имеющуюся у них вычислительную мощность.
Telegram ИИ Дайджест
#ai #llm #ml
Более масштабная цель Prism — это открытый ИИ, который работает на устройствах и более эффективно использует уже имеющуюся у них вычислительную мощность.
Telegram ИИ Дайджест
#ai #llm #ml
Using ternary weights {-1, 0, +1}, they built a family of models that are 9x smaller than their 16-bit counterparts while outperforming most models in their respective parameter classes on standard benchmarks.
Using ternary weights {-1, 0, +1}, they built a family of models that are 9x smaller than their 16-bit counterparts while outperforming most models in their respective parameter classes on standard benchmarks.
Video: https://twitter.com/prismml/status/2103259930614767643 (2/2)
CD (700 MB): PrismML Bonsai 4B (1-bit quant, trained from Qwen)
DVD (4.7 GB): Qwen 3.5 9B quantized to 3 bits/parameter
Blu-ray (25 GB): Gemma 4 31B quantized to 5 bits/parameter
CD (700 MB): PrismML Bonsai 4B (1-bit quant, trained from Qwen)
DVD (4.7 GB): Qwen 3.5 9B quantized to 3 bits/parameter
Blu-ray (25 GB): Gemma 4 31B quantized to 5 bits/parameter
PrismML has developed its compact 2B parameter LLMs for Qualcomm Snapdragon-powered smart glasses, shrinking larger models 4x while keeping performance.
A step towards on-device open-weight AI, though no glasses are announced yet. 👓
PrismML has developed its compact 2B parameter LLMs for Qualcomm Snapdragon-powered smart glasses, shrinking larger models 4x while keeping performance.
A step towards on-device open-weight AI, though no glasses are announced yet. 👓
https://gigazine.net/news/20260710-prismml-iphone-apple-qwen/
https://gigazine.net/news/20260710-prismml-iphone-apple-qwen/
PrismML, Qualcomm’un Snapdragon platformu için optimize edilmiş 1-bit Bonsai dil modelini duyurdu. Model akıllı gözlüklerde yerel olarak çalışabiliyor.
haber.com
PrismML, Qualcomm’un Snapdragon platformu için optimize edilmiş 1-bit Bonsai dil modelini duyurdu. Model akıllı gözlüklerde yerel olarak çalışabiliyor.
haber.com