ChatGPT vs 5 AI Models: Cost Shock

Key insights

• Copilot Cowork test compared the same prompt across six models (dashboard, PowerPoint, Word, email, ticketing, sentiment). The trial showed wide differences in quality and cost when the teams ran identical tasks.
  
• 11.7x cost gap was observed between the most expensive and cheapest model for the same outputs; Terra delivered better cost and Word-doc quality than GPT-5.5, while Opus 4.8 produced the strongest dashboard for the fewest credits.
  
• The practical recommendation: stop routing production Cowork traffic through GPT-5.5 and switch to Terra for similar or better output at lower credit cost.
  
• Microsoft unveiled the MAI family, led by MAI-Thinking-1 (a 35B-active-parameter reasoning model with a 256K context window) and I--1Flash (text-to-code specialist). The company claims roughly 10x lower token costs than comparable third-party models while keeping competitive performance.
  
• The new models use a Mixture of Experts (MoE) approach to reduce inference footprint; Microsoft deploys them on Azure and exposes standard APIs for easy integration into apps and workflows.
  
• Immediate impact: Microsoft already embeds these models in Excel and Outlook to cut third-party fees, and small Aion models can run locally on Windows PCs to enable offline or low-cost use. This shift boosts Microsoft’s strategic independence and lowers enterprise AI costs.
  

Keywords

AI model cost comparison, cost per prompt AI, prompt pricing comparison, cheapest AI model for prompts, GPT vs Llama cost comparison, AI inference cost comparison, reduce AI prompt costs, prompt engineering cost analysis