- Decision-1 focuses on non-generative tasks like classification, evaluation, and routing to optimize agent efficiency and control.
- Built on Qwen3.5-9B, it demonstrates the strategy of fine-tuning open-source small models for specific high-performance, low-cost scenarios.
- Aggressive pricing (free output tokens) indicates major players are competing fiercely for market share in agent infrastructure.
AI CURATED HOT STORY · 10/10/2026
Microsoft Launches Microsoft-Decision-1: A Post-Trained Qwen3.5-9B Model for Ultra-Low Latency Structured Decision Making
Microsoft has officially launched Microsoft-Decision-1, a model specifically designed for structured decision-making tasks, built upon post-training Alibaba's open-source Qwen3.5-9B. The core breakthrough lies in its ultra-low latency single-inference capability, achieving the highest accuracy in blind tests covering nearly 150,000 samples. Its response speed is 35 times faster than GPT-6 Sol, while passing multiple safety benchmarks to effectively intercept malicious behaviors and maintain high availability.
Cross-verification from multiple sources indicates that the model does not generate text but outputs strictly calibrated probability values, targeting high-frequency simple judgment needs such as intent recognition, content moderation, and agent routing. Compared to similar competitors, its inference speed is 4.5 times faster, with a decision flip rate of only 1.3% under perturbed inputs, demonstrating exceptional stability. Pricing is highly competitive at $0.042 per million input tokens (free output), with significant cost reduction effects already verified internally within Xbox and Copilot.
This release marks a critical evolution from generative reasoning to efficient execution-based decision-making, defining a new category of 'instant action.' Now available on Microsoft Foundry and soon on OpenRouter, it provides developers with a cost-effective solution for structured decisions, promising to significantly optimize the controllability and efficiency of automated processes in software systems.
Coverage timeline
Total 5 reports · Latest first- The DecoderT2·78 pts
- IT之家 · 智能时代T2·78 pts
- Microsoft released Microsoft-Decision-1, post-trained on Qwen3.5-9B for structured decision tasks
- Achieved highest accuracy across 36 benchmarks and is 35x faster than GPT-6 Sol
- Passed 11 security benchmarks, effectively blocking malicious inputs while maintaining usability
- Highly competitive pricing: $0.042 per million input tokens, free output
- OpenRouter (@OpenRouter)T1·68 pts
- Microsoft-Decision-1 is post-trained from Qwen3.5-9B, focusing on high accuracy and fast inference.
- Claims top accuracy across 36 blind benchmarks and 35x faster inference than GPT-6 Sol.
- Highly robust to input perturbations with only a 1.3% decision flip rate, priced at $0.042/M.
- 宝玉 (@dotey)T1·78 pts
- Clear positioning: Specializes in multiple-choice, classification, and scoring tasks without text generation, targeting high-frequency simple judgments in software.
- Significant performance gains: Approximately 35x faster than GPT-6 Sol and 4.5x faster than competitors, with high stability (only 1.3% result variation under perturbation tests).
- Core mechanism innovation: Outputs calibrated probability scores, enabling developers to set confidence thresholds for automatic execution or human escalation, enhancing workflow controllability.
- Hacker News AIT2·78 pts
- New Category: Distinguishes between generative LLMs and action-oriented decision models.
- Key Advantage: Achieves ultra-low latency and high cost-efficiency for routing, classification, and verification tasks.
- Ecosystem Integration: Available via Microsoft Foundry with upcoming OpenRouter support for easy developer access.