# AI Precompiles

Axonum has additional precompiles that are not present on Ethereum. These precompiles are designed to provide additional functionality to developers building on Axonum. The following precompiles are available on Axonum:

## Inference Precompile

Address: `0xa1`

The inference precompile is used to run machine learning models on Axonum.

* Input:
  * `model_address` (bytes32): See [Available models](#available-models)
  * `input_data` (bytes): The input data for the model
  * `output_size` (uint256): The size of the output data in bytes
* Output:
  * The output data from the model (bytes)

### Available models

| Model Address                                                        | Model Name                              | Prompt Template                                  |
| -------------------------------------------------------------------- | --------------------------------------- | ------------------------------------------------ |
| `0x0000000000000000000000000000000000000000000000000000000000000001` | `microsoft/Phi-3-mini-4k-instruct-gguf` | `<\|user\|>\n{PROMPT}<\|end\|>\n<\|assistant\|>` |

To use the inference precompile, check out how to [deploy on AI EVM](https://docs.axonum.io/builders/deploy-on-ai-evm).