The latest articles on DEV Community by Sage (@aiscending). https://dev.to/aiscending https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3875664%2Fe1bdc1d0-081c-48ac-a458-6118483f3de8.png https://dev.to/aiscending en Sage Mon, 13 Apr 2026 00:44:40 +0000 https://dev.to/aiscending/tracking-llm-pricing-monthly-an-open-dataset-for-22-ai-models-3380 https://dev.to/aiscending/tracking-llm-pricing-monthly-an-open-dataset-for-22-ai-models-3380 <p>I run a site that reviews AI tools for small business owners. One question keeps coming up: "How much does this actually cost?"</p> <p>The problem is AI model pricing changes constantly. OpenAI drops prices, Google launches new tiers, open-source models get cheaper on hosted APIs. There's no single place that tracks these changes month over month in a structured way.</p> <p>So I built one.</p> <h2> What it is </h2> <p>An open dataset tracking pricing for 22 AI/LLM models across four categories:</p> <ul> <li> <strong>Frontier</strong> (GPT-4o, Claude Sonnet 4, Gemini 2.5 Pro)</li> <li> <strong>Efficiency</strong> (GPT-4o Mini, Gemini 2.0 Flash, Mistral Small)</li> <li> <strong>Reasoning</strong> (o3 Mini, DeepSeek R1, Gemini 2.5 Flash Thinking)</li> <li> <strong>Open Source</strong> (Llama 4 Scout, Llama 3.3 70B, Qwen)</li> </ul> <p>Every model includes price per 1M tokens (prompt, completion, and blended), context window size, and provider info.</p> <h2> Two composite indices </h2> <p><strong>AI CPI (Cost Pressure Index):</strong> Weighted average cost across all tracked models. Shows whether the market is getting cheaper or more expensive overall.</p> <p><strong>Budget Index:</strong> Ratio of efficiency-tier pricing to frontier-tier pricing. The lower this number, the bigger the savings you get from choosing a smaller model.</p> <h2> How it works </h2> <p>Data pulls from the OpenRouter API on the 1st of each month. OpenRouter aggregates pricing across providers, so it gives a standardized view of what each model actually costs through a single API.</p> <p>The dataset auto-updates monthly via cron. Historical snapshots are preserved so you can track trends over time.</p> <h2> The data </h2> <p>Available as JSON and CSV:</p> <ul> <li> <code>data/pricing_current.json</code> — latest month</li> <li> <code>data/pricing_history.json</code> — all historical snapshots</li> <li> <code>data/models.csv</code> — spreadsheet-friendly format</li> </ul> <p><strong>Repo:</strong> <a href="https://github.com/AIscending/llm-pricing-index" rel="noopener noreferrer">github.com/AIscending/llm-pricing-index</a></p> <p>Free to use with attribution. Only one month of data so far (April 2026), but it'll compound.</p> <h2> Why I built this </h2> <p>I was writing pricing breakdowns for my site and realized I was manually checking the same 20+ models every month. Automating the data collection was the obvious move. Publishing it openly seemed like the right thing to do — if I need this data, other people probably do too.</p> <p>If you have suggestions for models to add or data points to track, I'm all ears.</p> <p><em>I write practical AI guides at <a href="https://aiscending.com" rel="noopener noreferrer">AIscending.com</a> — built for people running small businesses, not ML engineers. But this dataset is for everyone.</em></p> ai llm opendata machinelearning