Cost to Generate 1,000 Product Descriptions with LLM APIs

Each product description generation requires ~400 input tokens (product name, specs, features, brand guidelines) and ~800 output tokens (the description, ~600 words). Product description generation is output-heavy, so models with low output pricing are most cost-effective.

Formula: cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × quantity / 1,000,000

All prices are per million tokens, sourced directly from official provider pricing pages. No fabricated numbers — every model in the table links to its detail page, which cites the official pricing source.

How much does it cost to generate 1,000 product descriptions with an LLM?

It depends on the model. Product-description generation is output-heavy (~400 input / ~800 output tokens per product), so output price drives cost. The calculator above computes the exact current cost for every model, cheapest-first, from live per-million-token pricing — the table above ranks models by total cost for this output-weighted workload.

Which LLM is cheapest for generating product descriptions?

The cheapest are the models with low output pricing, which the calculator ranks cheapest-first for this output-heavy workload — so the top of the table is your lowest cost. Higher-tier models produce more creative, brand-aligned copy at a higher price.

How are product description token costs calculated?

Each product uses ~400 input tokens (specs) and ~800 output tokens (description). Total cost = (input_tokens × input_price + output_tokens × output_price) × number_of_products. Prices are per million tokens from official provider pricing.