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A brief overview of the costs associated with different AI models like Opus and QN, inference markets, and how to choose the right model to avoid hitting consumption limits.

AI Model Economics and Costs

01:20•Study Material
This lesson provides a quick snapshot of the economics and approximate costs associated with various AI models. It covers expensive models like Opus 4.6, OpenAI's competitive pricing drops, and Chinese models like QN and JLM that can theoretically be run on private infrastructure. The lesson also highlights inference markets like OpenRouter, where users pay per token. It emphasizes the importance of matching the model's cost and capabilities to the complexity of the task, warning that using an expensive model for trivial tasks can quickly exhaust monthly subscription limits and interrupt service.
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EconomicsCostOpus 4.6OpenAIQNJLMOpenRouterInference MarketsTokensConsumption limit