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Officially verified details LLMtrack

AI cost tracking for developers: what every LLM request costs the moment it completes, by feature, model and customer. SDK, no proxy, prompts never stored.

LLMtrack

LLMtrack Reviews and Details

This page is designed to help you find out whether LLMtrack is good and if it is the right choice for you.

Screenshots and images

  • Image date //
    2026-10-16
  • Image date //
    2026-10-16
  • Image date //
    2026-10-16
  • Image date //
    2026-10-16

Features & Specs

  1. Cost per feature

    Every LLM request is labelled with the product feature that made it, so spend splits by feature

  2. Cost per customer

    Spend per customer, compared with their plan price to show the margin on each account

  3. Model switch advice

    Benchmark-backed advice per feature: Switch, Test first or Keep

  4. Cache intelligence

    Cache hit rate and savings per feature, with an alert when caching breaks

  5. Spend forecast

    Projected monthly bill and the day you will cross your budget

  6. Image and audio models

    Images and voice are priced in tokens at their own rates; audio is never priced at text rates

  7. Unknown models

    Flagged as unpriced, never recorded as $0

  8. Gateway integrations

    Connects to OpenRouter, Cloudflare AI Gateway and LiteLLM with one URL, no SDK needed

  9. Real-time cost

    Each request is priced in under a second after it completes

  10. Component-level pricing

    Text input, cached reads, cache writes, reasoning, text output, audio in and audio out are each priced at their own rate

  11. Model price coverage

    420+ models from 12 providers, re-synced daily from each provider’s published rates

  12. SDKs

    Official Node.js (npm: llmtrack) and Python (PyPI: llmtrack-sdk) SDKs

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Questions & Answers

As answered by people managing LLMtrack.
  1. What makes LLMtrack unique?

    It shows what every LLM request costs the moment it completes, broken down by feature and customer. Each request is priced component by component, across 422 models. Unknown models are flagged, never shown as $0. No proxy, no prompts stored.

  2. Why should a person choose LLMtrack over its competitors?

    Most tools trace what your AI calls did. LLMtrack tells you which feature and which customer is costing you money, and what to change. Setup is one SDK call. The free plan includes every feature.

  3. How would you describe the primary audience of LLMtrack?

    Developers and small SaaS teams shipping AI features who get a provider's bill and can't tell which feature or customer caused it.

  4. What's the story behind LLMtrack?

    My OpenAI bill was one number. I wanted to know which feature spent it, so I built a small logger. By cost it was the code feature. By tokens it was the summarizer. Watching tokens alone would have blamed the wrong one.

  5. Which are the primary technologies used for building LLMtrack?

    Next.js, TypeScript, Vercel, Supabase (Postgres), Node.js and Python SDKs, OpenTelemetry.

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Is LLMtrack good? This is an informative page that will help you find out. Moreover, you can review and discuss LLMtrack here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.