Microsoft’s New AI Model Is 35x Faster and Up to 200x Cheaper Than GPT-6 Sol

Microsoft has introduced Microsoft-Decision-1, a small AI model designed to produce decisions between predefined options instead of generating long-form responses.

Key points

• Decision-1 was reportedly 2.5 times faster than H2O-Lightning-4B v1.1 and 35 times faster than GPT-6 Sol.
• Microsoft evaluated Decision-1 throughout 36 benchmarks containing almost 150, 000 questions that were kept blind from training.
• Xbox Notes It Was 14x Faster and 200x Cheaper Than GPT-6 Sol.
• Microsoft notes Decision-1 delivered quality competitive with GPT-6 Sol while being more than 14 times faster and around 200 times cheaper for that workload.
• While Decision-1 was around 100 times faster, according to Microsoft, its decision quality was competitive with GPT-5.6 Luna.

In practice, the model is based on Alibaba's open-weight Qwen3.5-9B and has been post-trained by Microsoft specifically for tasks such as classification, routing, verification, and workflow control.

Microsoft notes Decision-1 can outperform or match much larger general-purpose AI models on decision-focused workloads while running substantially faster and at a fraction of the cost.

Decision-1 receives a fixed set of feasible answers and assigns a calibrated probability score to each option.

It can handle yes/no questions, multiple-choice tasks, and ratings. Microsoft additionally designed it to evaluate AI responses or agent actions against a predefined rubric. Microsoft CEO Notes AI Models Need an Emergency Brake.

Unlike a conventional chatbot, Decision-1 is not designed to write essays, emails or conversational answers. Base Model Qwen3.5-9B. Context Window 32, 000 tokens. Primary Function Decision-making and classification. Output Probability scores throughout predefined choices. Input Cost $0.042 per 1 million tokens. Availability Microsoft Foundry, OpenRouter.

Microsoft warns that the model should not be the sole basis for high-impact decisions involving individuals, including areas such as employment or credit. Decision-1 Tops Microsoft's 36-Benchmark Test.

According to Microsoft, Decision-1 achieved the highest overall accuracy among the models included in its evaluation.

In practice, the firm additionally emphasized latency. Decision-1 was reportedly 2.5 times faster than H2O-Lightning-4B v1.1 and 35 times faster than GPT-6 Sol. Microsoft Decision Benchmark Results. Model Relative Speed vs Decision-1 Key Result. Microsoft-Decision-1 1x baseline Highest overall accuracy in Microsoft's 36-benchmark evaluation.

H2O-Lightning-4B v1.1 Decision-1 was 2.5x faster Runner-up in Microsoft's comparison. GPT-6 Sol Decision-1 was 35x faster Much larger general-purpose model. Jev Decision-1 was 2.8x faster Competing decision model.

Notably, the results come from Microsoft's own testing, so they should be interpreted within the company's benchmark methodology rather than as independent measurements. Only 1.3% Decision Change After Prompt Rewording.

Microsoft additionally tested how consistently Decision-1 responds when the same question is phrased or ordered differently.

In practice, the model changed its decision only 1.3% of the time on average when Microsoft reworded or reordered equivalent requests.

That consistency is particularly significant for tasks such as routing and automated workflows, where minor changes in phrasing should not produce completely different decisions. Questions evaluated Almost 150, 000. Average decision change after rewording/reordering 1.3%. Safety requests 5, 250.

Xbox Notes It Was 14x Faster and 200x Cheaper Than GPT-6 Sol. Microsoft has already tested Decision-1 in internal products and teams.

Xbox Research applied the model to categorize more than 10, 000 pieces of player feedback and reviews into different themes.

Microsoft notes Decision-1 delivered quality competitive with GPT-6 Sol while being more than 14 times faster and around 200 times cheaper for that workload. Metric Microsoft-Decision-1 vs GPT-6 Sol. Cost Up to 200x cheaper. Feedback Items Processed 10, 000+.

This employ case illustrates where specialized decision models could have an advantage. Sorting thousands of customer reviews does not necessarily require a sizeable model capable of generating complex prose. Copilot Test Demonstrates 100x Speed Advantage. Microsoft's Copilot team additionally evaluated Decision-1.

While Decision-1 was around 100 times faster, according to Microsoft, its decision quality was competitive with GPT-5.6 Luna. Internal Test Quality Comparison Speed Advantage. Xbox Research Competitive with GPT-6 Sol 14x+ faster. Microsoft Copilot Competitive with GPT-5.6 Luna 100x faster. Microsoft evaluated Decision-1 using 5, 250 prompts throughout 11 safety benchmarks. The evaluations covered areas including.

Decision models can be particularly significant in AI agent systems as they may be applied to approve, reject or route actions taken by another model.

While output tokens are free, microsoft has priced Decision-1 at just $0.042 per million input tokens. Token Type Cost per 1 Million Tokens.

In practice, the unusual pricing reflects the model's specialized purpose. Instead of producing hundreds or thousands of output tokens, it primarily returns scores for a predefined set of choices. This Free Android App Lets Claude Code Employ Your Phone. Microsoft Intends OpenAI and MAI-Based Versions.

Decision-1 at present uses Qwen3.5-9B as its foundation, but Microsoft states it intends to rebase the system on other models.

Future versions could employ OpenAI models as well as Microsoft's own MAI models.

Microsoft has not explained why it intends to maintain Decision-1 throughout multiple model families. Decision Models Are Becoming a Major AI Category.

Microsoft is entering an increasingly crowded market. While OpenAI has placed its Decisions API into public beta, typeSafe AI introduced Jev a number of weeks before Decision-1.

Cloudflare, Strands, Liquid AI, Perplexity and Snowflake are additionally developing decision-focused AI systems. Microsoft notes Decision-1 was 2.8 times faster than Jev in its latency benchmark.

Notably, the broader idea is straightforward: not every AI task requires a massive general-purpose model. For workloads where an AI only needs to choose the best option, route a request, or verify an action, smaller decision models could potentially deliver similar results with dramatically lower latency and cost. Stay Connected with ProPakistani.

Obtain the latest tech news, telecom insights, and product launches wherever you prefer. Follow on Google Discover. Follow on Google News Join WhatsApp. See more ProPakistani stories in Google Search and Top Stories.

Technology and Automotive Specialist covering the latest cars, smartphones, AI breakthroughs, and.

Taken together, the developments around microsoft's New AI Model Is 35x Faster and Up to 200x Cheaper point to a situation that is still moving, and the coming days should bring more clarity.