---
title: Custom LLM
slug: turbine-user-guide/custom-llm
docTags: 
createdAt: 2026-05-11T05:57:43.849Z
---

Starting Turbine 26.1.2 release you can use the **Custom LLM** tab under **Account Settings** to route **Hero AI** through a provider you manage instead of default platform routing.

:::hint{type="info"}
The **Custom LLM** tab appears only when the Custom LLM feature flag is enabled for your account and you have account administrator or super administrator access. To enable Custom LLM, contact Swimlane support.
:::

:::hint{type="info"}
Changing **Custom LLM** settings while Hero AI work is in progress (plan generation, playbook builder prompts, companion chat, and similar) applies the new routing to subsequent LLM requests in that operation. Wait for long-running jobs to finish before switching providers if you need a single model throughout one task.
:::

## Hero AI Native Action and Provider Changes

When you turn **Use Custom LLM Provider** on or off, or switch between default Swimlane routing and LiteLLM (or **Custom Bedrock** on **Turbine Platform**), existing [Hero AI Native Action](docId\:C4CKmT7fHXgjBtlXxOOC2) steps may still store a **modelId** from the previous configuration.

Starting in **26.2.0**:

- At **run time**, if the saved model is not in the current available models list, the action uses the **Small** model (the default for Hero AI Native Action — **Claude Haiku 4.5** on Swimlane-managed routing) so playbook runs are not blocked.
- In the action dialog, **Model Selection** shows **Previously Selected Model is not available** in red until you pick a valid model or use **Use Default Model**.

Review playbooks after changing Custom LLM settings. See [Hero AI Native Action](docId\:C4CKmT7fHXgjBtlXxOOC2) in [Hero AI Native Action](docId\:C4CKmT7fHXgjBtlXxOOC2).

## Tooltip on Use Custom LLM Provider

Starting in **26.2.0**, hover the info icon next to **Use Custom LLM Provider** on **Admin Panel > SETTINGS > Account > Custom LLM** for guidance similar to:

:::BlockQuote
When using this setting, Hero AI traffic is routed to your custom LLM. If your custom LLM is not available at run time, or if you enable this setting and later disable it, Hero AI native actions fall back to the default **Small** model so workflows are not disrupted. Review your automations and update model selections where needed.
:::

Exact tooltip text may vary slightly in the product UI.

| Section                                                                                            | Use when                                                                      |
| -------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- |
| [Turbine Cloud](https://docs.swimlane.com/custom-llm#turbine-cloud)                                | You use hosted **Turbine Cloud** and configure **LiteLLM**                    |
| [Turbine Platform — LiteLLM](https://docs.swimlane.com/custom-llm#turbine-platform)                | You use on-premises **Turbine Platform** with a LiteLLM proxy                 |
| [Turbine Platform — Custom Bedrock](https://docs.swimlane.com/custom-llm#configure-custom-bedrock) | You use on-premises **Turbine Platform** with your own Amazon Bedrock API key |

## Turbine Cloud

The **Custom LLM** tab on **Turbine Cloud** connects Hero AI to your **LiteLLM** proxy. You enter a URL and API key, fetch the model catalog from your proxy, then choose models from dropdown lists. **Turbine Cloud** does not show **Select Your Provider**; LiteLLM is the only option.

### Prerequisites

- **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM** is visible.
- LiteLLM base URL, API key, and a running LiteLLM-compatible endpoint that exposes a models list.

### Configure LiteLLM

1. Open **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM**.
2. Turn **Use Custom LLM Provider** on.
3. Enter **LiteLLM URL** (HTTPS base URL for your LiteLLM-compatible API).
4. Enter **API Key** (credential Turbine sends to LiteLLM).
5. Click **Fetch Models**. Turbine loads the models your proxy exposes and fills the model dropdowns below.
6. Select **Medium Model**, **Medium Model Fallback** (optional), **Small Model**, and **Small Model Fallback** (optional).
7. Click **Save**.

::Image[]{src="https://api.archbee.com/api/optimize/n8uUzk0MM4uC57-zlHNtY/a5r8VTrGqmtB0E5CSVhRB_custom-llm-tc.png" size="82" width="800" height="478" position="center" darkWidth="800" darkHeight="478" showCaption="false"}

| Field                     | Role                                                                                           |
| ------------------------- | ---------------------------------------------------------------------------------------------- |
| **Fetch Models**          | Retrieves the model list from your LiteLLM proxy after **LiteLLM URL** and **API Key** are set |
| **Medium Model**          | Primary model for medium-tier Hero AI workloads (companion, agents)                            |
| **Medium Model Fallback** | Optional fallback for the medium tier                                                          |
| **Small Model**           | Primary model for Hero AI Native Action (**Claude Haiku 4.5** when Swimlane-managed)           |
| **Small Model Fallback**  | Optional fallback for the small tier                                                           |

:::hint{type="info"}
**Fetch Models** is disabled until **LiteLLM URL** and **API Key** are entered. When you reopen saved settings, the UI fetches models automatically. After you change the URL or API key, click **Fetch Models** again before you save. If the request fails, Turbine shows **Failed to fetch models** and the dropdowns stay empty until you correct the connection and fetch again.
:::

**Tip:** Choose Sonnet-class models for **Medium Model** and Haiku-class models for **Small Model** when your LiteLLM catalog includes them (for example **sonnet45** and **haiku45** aliases).

## Turbine Platform

The **Custom LLM** tab on **Turbine Platform** supports two providers: **LiteLLM** or **Custom Bedrock**. Use **Select Your Provider** to choose which form the tab shows.

LLM routing can also be defined in the **Turbine Platform Installer** (for example LLM\_MODEL\_ID\_MEDIUM). Confirm with your Swimlane contact whether installer values or account settings take precedence in your cluster.

### Configure LiteLLM

**Prerequisites**

- **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM** is visible.
- LiteLLM base URL, API key, and a running LiteLLM-compatible endpoint that exposes a models list.

**Steps**

1. Open **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM**.
2. Turn **Use Custom LLM Provider** on.
3. Set **Select Your Provider** to **LiteLLM**.
4. Enter **LiteLLM URL**.
5. Enter **API Key**.
6. Click **Fetch Models**.
7. Select **Medium Model**, **Medium Model Fallback** (optional), **Small Model**, and **Small Model Fallback** (optional).
8. Click **Save**.

::Image[]{src="https://api.archbee.com/api/optimize/n8uUzk0MM4uC57-zlHNtY/Tvj4z648gNQriVM3g4mgl_custom-llm-tp.png" size="84" width="800" height="450" position="center" darkWidth="800" darkHeight="450" showCaption="false"}

| Field                     | Role                                                         |
| ------------------------- | ------------------------------------------------------------ |
| **Fetch Models**          | Loads models from LiteLLM into the dropdowns below           |
| **Medium Model**          | Used for the Hero AI Companion and AI SOC plan generation.   |
| **Medium Model Fallback** | Optional fallback for the medium tier                        |
| **Small Model**           | Used for the Hero AI Native Action and some AI SOC features. |
| **Small Model Fallback**  | Optional fallback for the small tier                         |

**LiteLLM URL**, **API Key**, **Medium Model**, and **Small Model** are required when custom LLM is enabled.

**Tip:** Use Sonnet-class models for medium tiers and Haiku-class models for small tiers when your LiteLLM catalog supports them.

### Configure Custom Bedrock

**Custom Bedrock** supports two configuration paths on **Turbine Platform**:

| Path                               | **Use Bedrock API Key** | Model entry                                                                                                                   |
| ---------------------------------- | ----------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
| **IAM / deployment credentials**   | Off                     | Click **Fetch Models**, then select models from dropdowns (same pattern as LiteLLM)                                           |
| **Bedrock API key (bearer token)** | On                      | Enter **Bedrock URL**, **Bedrock API Key**, and inference profile IDs manually in text fields (**Fetch Models** is not shown) |

### Custom Bedrock With IAM or Deployment Credentials

**Prerequisites**

- **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM** is visible.
- Bedrock access configured at deployment (IAM or cluster settings per your Swimlane contact).

**Steps**

1. Open **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM**.
2. Turn **Use Custom LLM Provider** on.
3. Set **Select Your Provider** to **Custom Bedrock**.
4. Leave **Use Bedrock API Key** off.
5. Click **Fetch Models**.
6. Select **Medium Model**, **Medium Model Fallback** (optional), **Small Model**, and **Small Model Fallback** (optional).
7. Click **Save**.

### Custom Bedrock With Bedrock API Key

**Prerequisites**

- **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM** is visible.
- Bedrock runtime URL, Bedrock API key, and cross-region **inference profile** IDs for each tier.

**Steps**

1. Open **Admin Panel** > **SETTINGS** > **Account** > **Custom LLM**.
2. Turn **Use Custom LLM Provider** on.
3. Set **Select Your Provider** to **Custom Bedrock**.
4. Turn **Use Bedrock API Key** on.
5. Enter **Bedrock URL** (runtime endpoint for your region, for example `https://bedrock-runtime.us-west-2.amazonaws.com`).
6. Enter **Bedrock API Key** (masked after save; leave blank to keep the stored key, or enter a new value to replace it).
7. Enter inference profile IDs in each **Medium Model**, **Small Model**, and optional fallback field (see below).
8. Click **Save**.

![](https://api.archbee.com/api/optimize/n8uUzk0MM4uC57-zlHNtY/5CJMwVbzTuOP0FjgMiMt1_custom-llm-bedrock.png)

:::hint{type="warning"}
Long-term Amazon Bedrock API keys can be configured to last longer than 12 hours. Swimlane recommends long-term keys only for exploratory use to reduce security risk in production.
:::

For **Custom Bedrock** without a Bedrock API key (for example IAM credentials configured at deployment), follow guidance from your Swimlane contact.

**Inference Profile IDs**

The UI prompts you to enter an **Inference Profile ARN** for each model. Use a cross-region inference profile ID, not a plain foundation model ID. Example: global.anthropic.claude-3-5-sonnet-20241022-v2:0.

| Field                     | Role                                                         |
| ------------------------- | ------------------------------------------------------------ |
| **Medium Model**          | Used for the Hero AI Companion and AI SOC plan generation.   |
| **Medium Model Fallback** | Optional fallback for the medium tier                        |
| **Small Model**           | Used for the Hero AI Native Action and some AI SOC features. |
| **Small Model Fallback**  | Optional fallback for the small tier                         |

The inference profile prefix (us., eu., jp., or so on.) must match the region group of your **Bedrock URL** endpoint. Bedrock API keys are valid for the Bedrock **runtime** only; mapping from a foundation model ID to an inference profile requires IAM control-plane access and does not run on the API key path.

When **Use Bedrock API Key** is on, **Medium Model**, **Small Model**, and the connection fields for your selected provider must be valid before save succeeds.

## Validation and Errors

**Turbine Cloud**

- Model and URL fields cannot contain characters blocked for injection safety: angle brackets, double quotation marks, apostrophe, ampersand, parentheses, curly braces, or semicolons.
- **LiteLLM URL** must be a valid URL pattern.
- When **Use Custom LLM Provider** is on, **LiteLLM URL**, **API Key**, **Medium Model**, and **Small Model** must be valid before save succeeds.
- If **Fetch Models** fails, correct **LiteLLM URL** and **API Key**, fetch again, then save.

**Turbine Platform**

- The same character and URL rules apply to **LiteLLM** and **Custom Bedrock** fields.
- For **LiteLLM** and for **Custom Bedrock** without **Use Bedrock API Key**, select models from the lists populated by **Fetch Models**.
- When **Use Custom LLM Provider** is on, all required connection and model fields for your selected provider must be valid before save succeeds.

**Both deployments**

- If save fails, read the notification and correct the indicated fields.