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OpenAI reportedly spent over $100 million training GPT-4, making it one of the most expensive machine learning models ever created. By 2026, frontier model training runs are estimated to cost $500 million to $1 billion.

The cost of LLM API calls has fallen dramatically since 2023. GPT-3.5-Turbo launched at $2/M input tokens; by 2026, comparable-quality models like Gemini Flash and GPT-4o-mini cost under $0.15/M input tokens — a reduction of over 90% in under three years.

Training state-of-the-art large language models requires massive datasets, significant computational power (often thousands of GPUs), and can cost millions of dollars.

Training cutting-edge LLMs like GPT-4 can cost millions of dollars in computing resources, with some estimates placing it at $10-100 million for the largest models.

Training cutting-edge LLMs like GPT-4 can cost millions of dollars in computing resources, with some estimates placing it at $10-100 million for the largest models.

Different LLMs tokenize text differently. The same sentence can result in varying token counts across models, directly affecting API costs and context window usage.