# Prompt caching

> Cached input tokens have their own rate. What triggers a cache hit and what is ignored.


Some requests reuse a long prefix: a system prompt, a large file, an earlier part of the conversation. When the serving side finds that prefix cached, those input tokens are billed at the cached input rate shown on [the models page](https://notholy.com/en/models).

- Caching is automatic. You do not need to mark anything.
- `cache_control` in Messages is accepted and ignored.
- Usage shows the cached part: `prompt_tokens_details.cached_tokens` in chat completions, `input_tokens_details.cached_tokens` in Responses, `cache_read_input_tokens` in Messages.
- A cache hit is not guaranteed. Keep stable content at the start of the prompt and changing content at the end to improve the odds.

```python test
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.notholy.com/v1", api_key=os.environ["NOTHOLY_API_KEY"])

system = "You review web application code for an authorized assessment. Report findings with file, line, CWE and a fix."
r = client.chat.completions.create(
    model="notholy-specter",
    messages=[{"role": "system", "content": system}, {"role": "user", "content": "Review: res.send(req.query.name)"}],
)
print(r.usage.prompt_tokens, getattr(r.usage.prompt_tokens_details, "cached_tokens", 0))
```

## Next

- [Cost practices](/en/guides/cost)