LLM Prices Fell Up to 80% in Months. Here's What to Change in Your Stack
Your LLM bill is probably wrong. Not because you can't count, but because the price list you budgeted against is months old. Since late June, OpenAI and Anthropic have cut API prices repeatedly, by up to 80% on some models. Max Woolf (minimaxir) laid out the timeline this week in a post that hit the HN front page . I pulled the numbers. Prices below are $ per 1M tokens, as input / output / cache…
LLM prices have dropped significantly over the past few months, with OpenAI and Anthropic reducing API prices by up to 80% on some models. Max Woolf analyzed the pricing changes and found that the rates have dropped dramatically, from $5 per 1 million tokens for GPT-5.6 Sol to $0.20 for Luna. The main reasons behind this price reduction include the availability of open weights, which serve as the baseline for pricing, switching costs being minimal, serving costs decreasing, and potential subsidies due to the financial struggles of the major labs.
As a result, the cost of LLM usage has dropped dramatically, making it possible for businesses to reprice their stacks and save a significant amount of money. To take advantage of these lower prices, businesses should re-evaluate their usage and consider switching to cheaper models for certain tasks, while keeping the more expensive models for more complex tasks.
Additionally, it's important to stay flexible and regularly check the price sheet to ensure that the business is not overpaying for LLM usage.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
