Show HN: Price Per Token – LLM API Pricing Data

Original Article ↗ Hacker News Discussion ↗

Existing tools & discoverability

  • Several commenters point out prior LLM price comparison tools (OpenRouter, llm-prices.com, Helicone, models.dev, llmprices.dev, etc.) and are surprised the author didn’t find them.
  • Some say they now just use OpenRouter or similar services to check prices instead of vendor pages.

Scope, completeness, and “low effort” debate

  • Strong criticism: site initially covers ~26 models from 3 big providers, omitting many popular ones (Mistral, Llama, Gemma, DeepSeek, Qwen, Groq, etc.) and prompt-cache pricing, leading some to call it “low effort” or “a mockup.”
  • Others strongly defend the project: they value the simplicity, clear UI/graph, and see it as a useful starting point that can be iterated on.
  • The author says they intentionally started small to gauge interest and plans to add many more models and cache pricing.

Token pricing complexity

  • Multiple comments argue that “price per token” alone is misleading:
    • Tokenizers differ between models; images and structured output can be billed differently.
    • Providers have batch pricing, off-peak pricing, context-window-based pricing, “thinking” vs non-thinking token prices, tiering, and implicit/explicit caching.
    • Same model via different providers can have very different prices; open models often vary widely in cost across hosts.
  • Some suggest the right unit is “cost of a standardized task run” rather than per-token price.

Requested features & enhancements

  • Cost calculator for custom input/output token counts and blended input/output metrics.
  • Benchmarks or leaderboards joined with pricing to show “bang for buck,” possibly per endpoint / API shape.
  • Periodic standardized tasks (summarization, coding) to estimate real query cost, with timestamps and historical trend tracking.
  • Additional metadata: context length, modalities, cache pricing, provider, tiered pricing, etc.
  • Monitoring/alerting on pricing changes as a potential paid service.

Data accuracy & maintenance

  • One pricing error (Gemini 2.5 Flash Lite) is called out; the initial defensive response and later correction spur discussion about tone and trust.
  • Several people discuss scraping APIs (e.g., OpenRouter, LiteLLM) and using agents/scrapers to keep a prices database continuously up to date.