---
date: 2024-12-20
title: Improved cost tracking
description: Langfuse now supports cost tracking all usage types such as cached tokens, audio tokens, reasoning tokens, etc.
author: Hassieb
ogImage: /images/changelog/2024-12-20-improved-cost-tracking.png
canonical: /docs/observability/features/token-and-cost-tracking
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the canonical documentation for this feature (https://langfuse.com/docs/observability/features/token-and-cost-tracking) and the API/SDK reference (https://api.reference.langfuse.com).

LLMs have grown more powerful by supporting multi-modal generations, reasoning, and caching. As LLM usage pricing departs from a simple input/output token count, we are excited that Langfuse now supports cost tracking for arbitrary usage types. Generation cost are now accurately calculated and displayed in the UI.

In the Langfuse UI, you can now create LLM model definitions with prices for arbitrary usage types. When ingesting generations, you can provide the units consumed for each usage type. Langfuse will then calculate the cost for each generation.

**Learn more about [cost tracking with Langfuse](/docs/model-usage-and-cost)**

<!-- agent-instructions -->

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## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2024-12-20-improved-cost-tracking.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.