> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Use Custom Models

> Future AGI allows you to use your own custom models. This is useful if you want to use a model that is tailor made for your use case.

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## Overview

Future AGI supports two integration modes:

1. **From Model Provider (Recommended):** Direct integration with supported providers (OpenAI, AWS Bedrock, AWS SageMaker, Vertex AI, Azure), optimized for reliability, automatic updates, and simpler credential management.

2. **Configure Custom Model (Advanced):** Full flexibility to connect any model hosted behind an API endpoint, including in-house deployments, fine-tuned models, or proxy endpoints.

Once added, models are available platform-wide for custom evaluations.

<Tip>
  Click [here](/future-agi/get-started/evaluation/create-custom-evals) to learn how to create custom evaluations in Future AGI.
</Tip>

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## Adding Models from Supported Providers

Future AGI currently supports:

1. **OpenAI**
2. **AWS Bedrock**
3. **AWS SageMaker**
4. **Vertex AI**
5. **Azure**

* Each provider has provider-specific authentication and cost configuration fields.

* Set custom name to the model you are adding.

* Provide input and output token costs for the model to compute cost when performing evaluations in Future AGI.

### 1. OpenAI

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/1.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=030af5c4162f16ccc9f1ed5bc66dde41" alt="openai" width="1116" height="1476" data-path="images/custom-model/1.png" />

### 2. AWS Bedrock

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/2.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=d57500c76ac2304903dd9ce374d40494" alt="aws-bedrock" width="1116" height="1476" data-path="images/custom-model/2.png" />

### 3. AWS SageMaker

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/3.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=e3143cc3a4c2345218eea1a6595b36d2" alt="aws-sagemaker" width="1116" height="1476" data-path="images/custom-model/3.png" />

### 4. Vertex AI

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/4.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=5fb0222a60b0ba4266264e446556ce67" alt="vertex-ai" width="1116" height="1476" data-path="images/custom-model/4.png" />

### 5. Azure

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/5.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=d6a4e08aab1cfb1354db405dead27512" alt="azure" width="1116" height="1476" data-path="images/custom-model/5.png" />

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## Configuring Custom Model (Advanced)

Use this when integrating self-hosted models, fine-tuned endpoints, or third-party APIs.

<img src="https://mintcdn.com/futureagi/T0dFHFFalPtKA-do/images/custom-model/6.png?fit=max&auto=format&n=T0dFHFFalPtKA-do&q=85&s=e80fc14a6f5e5bfcdac1c9435e8fc7ae" alt="add-model" width="1116" height="1476" data-path="images/custom-model/6.png" />

***

| **Field**                                                         | **About**                                                                                                                         | **Explanation**                                                                                                                                 | **Example**                                                                 |
| ----------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- |
| **Model Name**                                                    | A friendly identifier for your model within Future AGI. This name appears in model selectors, dashboards, and evaluation reports. | Helps differentiate between multiple models, environments, and versions. Ensures better organization when running evaluations or RAG pipelines. | `mistral-rag-prod`                                                          |
| **Input Token Cost per Million Tokens**                           | The cost of input tokens (tokens sent in the request) per 1 million tokens.                                                       | Enables accurate billing visibility, cost attribution, and usage analytics within Future AGI dashboards.                                        | `1.50` *(represents \$1.50 per 1M input tokens)*                            |
| **Output Token Cost per Million Tokens**                          | The cost of output tokens (tokens generated in the response) per 1 million tokens.                                                | Used to calculate total request costs alongside input tokens. Critical for cost optimization and reporting.                                     | `2.00` *(represents \$2.00 per 1M output tokens)*                           |
| **API Base URL**                                                  | The endpoint where Future AGI sends API requests to communicate with your custom model.                                           | Required for model integration — Future AGI uses this endpoint for evaluations, RAG queries, prompt generation, and agent calls.                | `https://api.my-model-server.com/v1`                                        |
| **Add Custom Configuration** <br /> *(Custom Key & Custom Value)* | Lets you define custom headers, query parameters, or metadata required by your API.                                               | Needed for scenarios like authentication, multi-tenant routing, model versioning, or passing provider-specific parameters.                      | **Custom Key:** `Authorization` <br /> **Custom Value:** `Bearer sk-123456` |

***