Microsoft带着 Decision-1 挤进决策模型赛道：基于 Qwen3.5-9B，号称 36 个基准近 15 万题最准、比第二快 H2O-Lightning-4B 快 2.5 倍，输入 $0.042/百万、输出免费
Microsoft's Decision-1 model enters the fast-growing AI decision model race
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导读
Microsoft有了自己的决策模型。与 OpenAI、Cloudflare 以及这一品类「原创者」Jev 的同类产品一样，Decision-1 为快速、结构化的决策而建：Microsoft称它处理分类、评估与路由决策，并「有潜力」引导和控制智能体穿越复杂环境。技术底子与口径都给得明确：Decision-1 基于 Qwen3.5-9B；Microsoft说它是自家在覆盖近 15 万道题的 36 个基准上测得最准的模型；速度上比第二快的 H2O-Lightning-4B 快 2.5 倍。文章也点出一处比较上的缺口：同样基于 Qwen 的 Cloudflare 开源 Clef 模型并未被纳入对比。可用性与价格是输入每百万 token 0.042 美元、输出免费，经 Microsoft Foundry 与 OpenRouter 提供。结尾的判断颇有意味：9 月中凭 Jev 带火决策模型这条赛道的创业公司，最近几周恐怕不好过——这个点子扩散得很快，而技术很快就被用开放的小语言模型改写并超越了。
推荐理由
大厂跟进会把一个新品类从噱头推向常规选型，而输入计价、输出免费这一条定价写法本身值得注意。
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正文
Microsoft now has its own decision model. Like the ones from OpenAI , Cloudflare , and the "original" from Jev , Decision-1 is built for fast, structured decisions. According to Microsoft , it handles classifications, evaluations, and routing decisions and has "the potential" to "guide and control agents through complex environments."
Decision-1 is based on Qwen3.5-9B. Microsoft says it's the most accurate model tested across 36 benchmarks covering nearly 150,000 questions. On speed, it's 2.5 times faster than the runner-up, H2O-Lightning-4B. Cloudflare's open-source Clef models, which are also based on Qwen, weren't included in the comparison.
Decision-1 is available through Microsoft Foundry and OpenRouter . Input tokens cost $0.042 per million, and output tokens are free. Jev, the startup that kicked off the decision model trend in mid-September, has likely had a rough few weeks. The idea caught on fast, but the tech was quickly adapted and surpassed using open small language models.