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On October 9, Microsoft launched the Microsoft-Decision-1 decision model. The model does not generate text; instead, it performs a single forward-pass scoring of preset answer options and returns a calibrated probability for each option, and can be used for routing, classification, prioritization, and verification. The model is post-trained on Alibaba's Qwen3.5-9B, is in public beta on Microsoft Foundry, and is available on OpenRouter under the identifier microsoft/microsoft-decision-1; its weights are not distributed publicly. Microsoft says it achieved 83.5% accuracy on 36 benchmarks and about 150,000 held-out questions, and plans to later migrate the base to MAI and OpenAI models. The OpenRouter listing shows a price of $0.042 per million input tokens and free output. Other reports say it is 2.5 times faster than the second-place H2O-Lightning-4B.
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Microsoft releases the Decision-1 decision scoring model, post-trained on Qwen3.5-9BDevelopments
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Oct 11
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Microsoft releases the Decision-1 decision scoring model, post-trained on Qwen3.5-9B
On October 9, Microsoft launched Microsoft-Decision-1, which does not generate text but instead performs a single forward-pass scoring of preset answer options and returns a calibrated probability for each option, for use in routing, classification, prioritization, and verification. The model is post-trained on Alibaba's Qwen3.5-9B, is in public beta on Microsoft Foundry, and is available on OpenRouter under the identifier microsoft/microsoft-decision-1, with weights not distributed externally. Microsoft says it achieved 83.5% accuracy across 36 benchmarks and about 150,000 held-out questions, and plans to later migrate the base to MAI and OpenAI models; the OpenRouter listing shows a price of $0.042 per million input tokens, with output free.
Oct 10
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