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

> ## Agent Instructions
> For Fireworks Nexus, start at https://docs.fireworks.ai/nexus.
> Use https://docs.fireworks.ai/nexus/quickstart for coding harnesses, custom agents, APIs, SDKs, and LLM gateways.
> Use https://docs.fireworks.ai/nexus/firerouter for how model routers work, the supported model list, composition, closed-model credentials, and pricing.
> Prefer canonical short model IDs such as firerouter/opus. In LiteLLM litellm_params.model, use the full path fireworks_ai/accounts/fireworks/routers/firerouter/opus.
> Family names such as opus track the latest evaluated family version; do not describe them as fixed model versions.

# Microsoft Foundry

> Deploy frontier open models inside your Azure subscription, billed through Azure.

Fireworks AI is a first-party inference provider inside Microsoft Foundry. You can access frontier open models through your existing Azure account, with usage billed through Azure and counting toward your Microsoft Azure Consumption Commitment (MACC).

This page covers the Fireworks side of the integration. For Azure portal setup steps, see the [Microsoft Learn guide](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models).

<Info>
  **New to Fireworks?** Foundry users get the same OpenAI-compatible API and model catalog as direct Fireworks customers. Start with the [PayGo quickstart](#paygo-quickstart) below. You can be making requests in about 10 minutes.
</Info>

## Prerequisites

* An active Azure subscription
* The Fireworks integration enabled at the subscription level (see below)
* A Microsoft Foundry project with the **Azure AI Developer** role assigned

### Opt-in

Fireworks on Foundry requires a one-time opt-in per Azure subscription before you can create deployments. Follow the steps in the [Microsoft Learn guide](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models#enable-fireworks-on-foundry).

## Deployment modes

Fireworks on Foundry supports three deployment modes.

| Mode | Also called | Pricing | Regions | Right for |
| - | - | - | - | - |
| **PayGo** | Serverless, Data Zone Standard | Per token, MACC-eligible | US Data Zone only | Prototyping, low-volume workloads |
| **PTU** | Provisioned Throughput | Per PTU-hour, ACD + MACC eligible | Global | Production workloads with consistent traffic |
| **Custom Models** | Bring Your Own Model | PTU pricing | Global (PTU regions) | Trained model deployment |

PTU deployments can be created directly in the Azure portal. For help with PTU sizing on Fireworks models, [contact us](https://fireworks.ai/contact).

## Available models

All models use the OpenAI-compatible chat completions API and are added to the catalog on a rolling basis. For the current list of available models, see the [Microsoft Learn catalog](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models#available-catalog-models).

Chat completions only. Embeddings, image generation, and audio modalities are not available through Foundry.

## PayGo quickstart

PayGo (Data Zone Standard) is available in: East US, East US 2, Central US, North Central US, West US, West US 3.

The throughput limit for PayGo deployments is **500,000 tokens per minute (TPM)**. For higher limits, submit a limit increase request on [aka.ms/fireworks-quota](https://aka.ms/fireworks-quota) and [contact us](https://fireworks.ai/contact).

### Make your first request

Foundry deployments use an OpenAI-compatible endpoint. Use your Foundry project endpoint and Azure API key.

```python theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://<your-project>.services.ai.azure.com/models",
    api_key="<your-azure-api-key>",
)

response = client.chat.completions.create(
    model="fireworks-ai/FW-GLM-5.2",
    messages=[{"role": "user", "content": "Hello"}],
)

print(response.choices[0].message.content)
```

Find your project endpoint in the Microsoft Foundry portal under **Project settings**.

## PTU (Provisioned Throughput)

PTU deployments provide dedicated GPU capacity reserved for your workload, with consistent throughput and global region availability.

* Dedicated capacity, not shared with other tenants
* Available globally, not limited to US Data Zone
* ACD-eligible and MACC-eligible

You can create a PTU deployment directly in the Azure portal. For more on provisioned throughput, see the [Microsoft Learn guide](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/provisioned-throughput).

For help with PTU sizing on Fireworks models, [contact us](https://fireworks.ai/contact).

## Custom Models

Train on Fireworks and deploy on Foundry, or bring your own weights from wherever you post-train to deploy on Foundry. Your model is served on Fireworks infrastructure within Azure, billed through your Azure account.

### Supported base architectures

For the list of supported custom model architectures, see the [Microsoft Learn guide](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models#supported-model-architectures).

### Deployment

To import and deploy a custom model, follow the [Import custom models into Foundry guide](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/import-custom-models?tabs=rest-api).

## Billing

All Fireworks on Foundry usage is billed through Azure. You do not need a separate Fireworks billing account or contract.

* PayGo and PTU usage is MACC-eligible
* PTU deployments are ACD-eligible and qualify for quota retirement
* Direct Fireworks usage at [fireworks.ai](https://fireworks.ai) is billed separately and does not count toward MACC

## Troubleshooting

| Issue | Resolution |
| - | - |
| Quota exceeded error | Request a limit increase at [aka.ms/fireworks-quota](https://aka.ms/fireworks-quota) |
| Access denied on deployment | Verify you have the **Azure AI Developer** role on the project |
| Opt-in not propagating | Allow up to 30 minutes after registering `Fireworks.EnableDeploy` |
| Custom Model deployment failing | Confirm weights are full-weight (not LoRA adapters) and the architecture is in the [supported list](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models#supported-model-architectures) |
| PTU provisioning questions | [Contact us](https://fireworks.ai/contact) |

## Coding harnesses

Use your Foundry deployments from Claude Code, OpenCode, Cursor IDE, VS Code, and other coding harnesses.

<Card title="Foundry for Coding Harnesses" icon="terminal" href="/nexus/microsoft-foundry">
  Connect with FireConnect, configure a harness manually, or route Claude Code
  through an LLM gateway.
</Card>

This page covers enabling and operating Fireworks models in Foundry itself.

## Additional resources

* [Enable Fireworks on Foundry (Microsoft Learn)](https://learn.microsoft.com/en-us/azure/foundry/how-to/fireworks/enable-fireworks-models)
* [Microsoft Foundry portal](https://ai.azure.com/)
* [Fireworks training docs](/fine-tuning/finetuning-intro)
* [Fireworks Trust Center](https://fireworks.ai/trust)
* [Contact us](https://fireworks.ai/contact) for PTU provisioning and Custom Model support