PrismML compresses 9-billion-parameter model weights to 2GB: iPhones generate 34 tokens per second locally.
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Beating AI Express (Insight) – U.S. AI firm PrismML has rolled out three new models for its Bonsai 2 family: 2B, 4B, and 9B, all based on Alibaba’s Qwen3.5. The team restricted the language model’s core weights to only three values: -1, 0, and +1, cutting the model sizes to 0.43GB, 0.95GB, and 2GB respectively – roughly one-ninth the size of original 16-bit weight models. The new models retain support for inference, image understanding, and tool calling, and are primarily designed for local agents on devices like smartphones and personal computers. PrismML states that on the iPhone 18 Pro Max, the 9B model generates up to 34 tokens per second, while the 2B model hits 120 tokens per second. Official tests show the 9B model’s programming and instruction-following capabilities are nearly on par with the same-scale original Qwen3.5, though it lags significantly on complex tasks. In Tau2Bench, which assesses multi-turn dialogue and tool operations, Bonsai 2 9B scores 73.02, compared to the original model’s 85.25; its complex document parsing score is 73.8, versus 88.73 for the original. All three models have released their weights under the Apache 2.0 license.
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