Observed Signal · Apr 13, 2026 · Technical Release · Source: DEV Community · Impact: 2/5 · Sentiment: Positive
Open Dataset Tracks Monthly LLM Pricing for 22 Models
An author at AIscending published an open dataset that tracks monthly pricing and metadata for 22 LLM/AI models across four tiers (Frontier, Efficiency, Reasoning, Open Source). Each model record includes price per 1M tokens (prompt, completion, blended), context window size, and provider information. The dataset is updated automatically on the 1st of each month by pulling standardized pricing from the OpenRouter API and preserves historical snapshots. The project exposes two composite indices—AI CPI (Cost Pressure Index) and a Budget Index—that summarize market-wide cost trends and efficiency-to-frontier savings. Data files (JSON/CSV) and the repo (github.com/AIscending/llm-pricing-index) are openly available with attribution; the initial snapshot covers April 2026.
Provides an open, standardized monthly dataset and cost indices for LLM pricing, useful for teams evaluating model selection and cost trends but not a major platform policy or industry-shifting announcement.
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Key Takeaways & Evidence Grounding
- Open dataset tracks pricing for 22 AI/LLM models grouped into four categories: Frontier, Efficiency, Reasoning, Open Source.
- Each model entry includes price per 1M tokens (prompt, completion, blended), context window size, and provider information.
- Two composite indices published: AI CPI (Cost Pressure Index) and Budget Index (efficiency-tier to frontier-tier pricing ratio).
- Data is pulled monthly on the 1st from the OpenRouter API and historical snapshots are preserved via cron.
- Repository and data files available at github.com/AIscending/llm-pricing-index; initial data snapshot is April 2026.
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