Microsoft Launches Decision-1 AI Model: 35x Faster, 200x Cheaper Than GPT-6 Sol for Business Tasks

Microsoft Enters the Decision Model Race

Microsoft has launched Microsoft-Decision-1, a specialized AI model built for structured business decisions that promises to deliver results 35 times faster than GPT-6 Sol at a fraction of the cost1

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. The move positions Microsoft in the rapidly expanding decision models in AI category, joining over 100 similar models now competing for attention. Unlike traditional large language models that generate text or handle complex reasoning, Microsoft-Decision-1 focuses on selecting predefined options and assigning probability scores to possible outcomes, making it ideal for agentic AI applications and workflow automation.

Built on Chinese Technology with Plans to Shift

Microsoft-Decision-1 is based on Qwen3.5-9B, a model developed by Alibaba Cloud, the cloud computing division of Chinese tech giant Alibaba1

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. The model has undergone specialized post-training to enhance decision scoring capabilities2

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. However, Microsoft plans to rebase Decision-1 on its own models and those from OpenAI in the near future, though the company has not disclosed specific reasons for the initial reliance on the Chinese-developed foundation1

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. This strategic pivot suggests Microsoft aims to reduce dependencies while maintaining the performance advantages demonstrated in early testing.

Performance Benchmarks and Cost Advantages

According to Microsoft's published findings, Decision-1 achieved first place in accuracy across 36 benchmark tests covering nearly 150,000 questions, scoring 83.5 percent1

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. The model ranks second behind Quyet-1.0-Large in confidence score at 92.2 percent while delivering median-latency performance 4.5 times faster than that competitor1

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. In speed comparisons, Microsoft claims Decision-1 operates 2.5 times faster than H2O-Lightning-4B and 2.8 times faster than Jev in latency tests1

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. The pricing structure offers a cost-effective alternative at $0.042 per million input tokens with free output tokens, making it more than 20 times cheaper than GPT-6 Sol for text classification tasks1

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Real-World Testing and Business Applications

Microsoft's Xbox Research team conducted practical testing of Decision-1 on more than 10,000 pieces of game feedback and reviews2

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. The results showed quality comparable to GPT-6 Sol while operating more than 14 times faster and at approximately one-two-hundredth of the cost. The model handles structured business decisions including yes/no determinations, multiple choice selections, rating assessments, and rubric evaluations. Practical applications span content classification, job application routing, task prioritization, quality control, outcome validation, and safety checks2

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. For AI agent workflows, Decision-1 can determine whether tasks should proceed, require repetition, need escalation, or demand human intervention.

Security Evaluation and Availability

Microsoft conducted security testing on Decision-1 for harmful-content identification, jailbreak attempts, and prompt injection vulnerabilities2

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. The company evaluated consistency under varying input conditions, reporting an average decision-change probability of 1.3 percent across eight perturbation methods. These findings are based on Microsoft's internal evaluations and await independent validation. Achint Srivastava, VP of software engineering in the Office of the CTO at Microsoft, emphasized that "cost plays a major role in how people decide to use AI" and stressed the importance of choosing the right model for specific tasks1

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. Decision-1 is currently available through Microsoft Foundry, with access via OpenRouter planned for the near future1

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. Independent assessments will determine whether the reported speed, accuracy, and cost advantages hold up across diverse real-world applications.