PrismML

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PrismML

PrismML

@PrismML

Centering AI research on efficiency. https://t.co/88MQHGCeFD

United States Beigetreten Mart 2025
15 Folgt6.7K Follower
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PrismML
PrismML@PrismML·
Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.
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AnythingLLM
AnythingLLM@AnythingLLM·
Today, we demoed @PrismML's Bonsai 8B model in @AnythingLLM desktop to see if the 1-bit mode arch is the revolution local AI needs. Turns out, this is not an April fools joke. 1.1GB memory footprint for a whole 8B model with high accuracy
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うみゆき@AI研究
うみゆき@AI研究@umiyuki_ai·
おおっ!!なんかすごそうだぞ!PrismMLが1-bitBonsaiってモデルをオープンでリリース!ライセンスはApache。1.7Bと4Bと8Bの3種類がmlxとggufで公開!何がヤバいかってパラメータ当たりのサイズが1bitだという!つまり1bitネイティブ量子化モデル!8Bパラなのにモデルサイズ1.16GBしかなくてマジで1bit!1bitってゼロとイチしかないって事でしょ?そんなんでええんか。それでいてベンチスコアはLlama3.1-8B超えでQwen3-8Bよりは下と言うレベル。とはいえQwen3-8Bを1bit量子化なんて不可能なわけだから。速度も爆速でRTX4090で368tps!初日からLlama.cppでサポート済み!
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Tushar Bansal
Tushar Bansal@tushar_bans·
The journey to the next phase of AI will not only be about maximizing intelligence, but dramatically concentrating it from its current state. In 1976, Seymour Cray introduced the world to the Cray-1. It was a 5.5-ton, C-shaped monolith that redefined the limits of computation. Problems that once required the resources of entire institutions suddenly became tractable. Scientific discovery accelerated. Weather modeling improved. Physics, defense, and engineering entered a new era because unprecedented compute had been made real. Today, a processor thousands of times more powerful sits in your pocket. AI will follow the same arc. Right now, we are still in the "supercomputer era" of intelligence: extraordinary capability, but concentrated in a few hands and mediated by enormous infrastructure. That is not the endpoint. The true measure of progress will be defined by intelligence density: how much intelligence the world can hold, carry, and wield.
PrismML@PrismML

Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.

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nisten🇨🇦e/acc
it actually got half of my standard very hard question right even when running it in 8 bit kv cache activations: command used: llama.cpp/build/bin/llama-cli -m ~/1bit/Bonsai-8B.gguf -c 12000 -ngl 99 -t 4 --mlock --chat-template chatml -cnv -p "You are a helpful assistant.that thinks in first principles" --temp 0.5 -ctk q8_0 -ctv q8_0 Prompt: calculate how long a mass driver rail would need to be to accelerate people comfortably at max 2Gs on mars travelling along the slope of and launching from the top of mount olympus mons and what speed would it need to achieve at the top in order to get to escape velocity from Mars' gravity well or to at least get to the minimum martian orbital speed. Do thorough calculations with actual numbers and facts. Use emojis and pointform to communicate it all /think
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Kanu Gulati @Khosla Ventures
AI isn’t just a scale race anymore. It’s an efficiency war. The winners will be the ones squeezing the most intelligence out of every watt and every dollar i.e. Intelligence Density. That’s @PrismML bet. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GB of memory and delivers over 10x the intelligence density of its full-precision counterpart. This rewrites the economics of AI. @khoslaventures @vkhosla @SStrohband and I are thrilled to back this team: @BabakHassibi, @SahinLale, @HessianFree, @rsadri_ml
PrismML@PrismML

Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.

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PrismML
PrismML@PrismML·
Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.
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Flem
Flem@GrahamFleming·
@PrismML Pied Piper compression algorithm IRL
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