---
title: "Custom Models"
description: "How to configure custom or unlisted models for any provider"
platform: new
---

# Custom Models

Kilo Code ships with a curated list of models for each provider, but you can use **any model** your provider supports — including models that aren't in the built-in list. This is useful for:

- Using a newly released model before it's added to the built-in catalog
- Running a custom or fine-tuned model via LM Studio, Ollama, or another local provider
- Connecting to a self-hosted model behind an OpenAI-compatible API
- Configuring model-specific options like token limits, pricing, or reasoning settings

## Defining a Custom Model

Add custom models under the `provider.<provider_id>.models` key in your config file. The model key becomes the model ID you reference elsewhere.

{% tabs %}
{% tab label="VSCode" %}

1. Open **Settings** (gear icon) and go to the **Providers** tab.

2. Scroll to the bottom of the provider list and click **Custom provider**.

![Custom provider button in the Providers tab](/docs/img/custom-models/custom-provider-button.png)

3. Fill in the custom provider dialog:

![Custom provider configuration dialog](/docs/img/custom-models/custom-provider-details.png)

- **Provider ID** — A unique identifier using lowercase letters, numbers, hyphens, or underscores (e.g., `myprovider`). This becomes the `provider_id` in the `provider_id/model_id` format.
- **Display name** — A human-readable name shown in the UI (e.g., `My AI Provider`).
- **Base URL** — The OpenAI-compatible API endpoint (e.g., `https://api.myprovider.com/v1`). When a valid URL is entered, Kilo automatically fetches available models from the endpoint.
- **API key** — Your provider's API key. Optional — leave empty if you manage authentication via headers.
- **Models** — Add models manually by ID and display name, or select from the auto-fetched list that appears after entering a valid base URL.
- **Headers** (optional) — Add custom HTTP headers as key-value pairs if your provider requires them.

4. Click **Submit** to save. Your custom provider appears in the provider list and its models become available in the model picker.

To edit an existing custom provider, click the **Edit provider** button next to it in the connected providers section.

For additional model configuration (token limits, tool calling, reasoning, variants), edit the `kilo.jsonc` config file directly — see the **CLI** tab for the format.

{% /tab %}
{% tab label="CLI" %}

**Config file** (`~/.config/kilo/kilo.jsonc` or `./kilo.jsonc`):

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "lmstudio/my-custom-model",
  "provider": {
    "lmstudio": {
      "models": {
        "my-custom-model": {
          "name": "My Custom Model",
        },
      },
    },
  },
}
```

{% /tab %}
{% /tabs %}

The `model` key uses the format `provider_id/model_id`, where:

- **`provider_id`** is the key under `provider` (e.g., `lmstudio`, `ollama`, `openai`, `anthropic`, `openai-compatible`)
- **`model_id`** is the key under `provider.<provider_id>.models` (e.g., `my-custom-model`)

## Model Configuration Fields

All fields are optional. When a model ID matches one already in the built-in catalog, your values are merged on top of the defaults — you only need to specify what you want to override.

| Field | Type | Description |
|---|---|---|
| `name` | `string` | Display name shown in the model picker |
| `id` | `string` | API-facing model ID sent to the provider. Defaults to the config key |
| `tool_call` | `boolean` | Whether the model supports tool/function calling |
| `reasoning` | `boolean` | Whether the model supports extended thinking |
| `temperature` | `boolean` | Whether the model supports the temperature parameter |
| `attachment` | `boolean` | Whether the model supports file attachments |
| `modalities` | `object` | Optional. Supported input and output types: `{ input, output }` |
| `limit` | `object` | Token limits: `{ context, output, input? }` |
| `cost` | `object` | Pricing per million tokens: `{ input, output, cache_read?, cache_write? }` |
| `options` | `object` | Arbitrary provider-specific model options |
| `headers` | `object` | Custom HTTP headers to include in requests |
| `provider` | `object` | Override `{ npm?, api? }` — the AI SDK package or base API URL for this model |
| `variants` | `object` | Named variant configurations (e.g., different reasoning efforts) |

### Modalities (modalities)

The `modalities` object declares which content types the model can receive and produce. It is optional — omit it to use defaults from the catalog or fallback to text-only. When `modalities` is provided, both `input` and `output` arrays are required. Each array can include `text`, `image`, `audio`, `video`, or `pdf`.

| Sub-field | Type | Required | Description |
|---|---|---|---|
| `input` | `array` | Yes (if present) | Content types the model accepts from the user |
| `output` | `array` | Yes (if present) | Content types the model can generate in response |

For a standard text model that can also inspect images, use:

```jsonc
"modalities": {
  "input": ["text", "image"],
  "output": ["text"]
}
```

If `modalities` is omitted and the model ID matches a models.dev catalog entry for that provider, Kilo uses the catalog's modalities. For completely custom models with no catalog match, Kilo defaults to text input and text output only. Set `attachment: true` alongside image, audio, video, or PDF input modalities when the provider supports sending those files as attachments.

### Token Limits (limit)

The `limit` object controls how Kilo manages the model's context window and output length. These values are specified in **tokens**.

| Sub-field | Type | Required | Description |
|---|---|---|---|
| `context` | `number` | No | The model's total context window size (e.g., `131072` for a 128K model). Used to determine when conversation history should be compacted to stay within the window. |
| `output` | `number` | No | The maximum number of tokens the model can generate in a single response. Sent to the provider as `max_tokens` or equivalent. Capped at 32,000 by default. |
| `input` | `number` | No | An optional stricter input limit. Some providers enforce an input token ceiling that is lower than the full context window. When set, compaction triggers against this value instead of `context`. |

```jsonc
"limit": {
  "context": 131072,
  "output": 16384
}
```

If a model stops because it reaches `limit.output`, Kilo shows a visible warning that the response may be incomplete. For reasoning models that spend the whole response reasoning and produce no text or tool call, the warning suggests disabling reasoning or increasing `limit.output`.

#### How limits are resolved

Kilo resolves token limits in this order:

1. **Your config** — values you set under `provider.<id>.models.<model>.limit`
2. **Built-in catalog** — Kilo ships a snapshot of [models.dev](https://models.dev) and refreshes it hourly. If your model ID matches a known model, catalog values are used as defaults.
3. **Fallback** — if neither source provides a value, `context` and `output` default to `0`.

#### What happens when limits are `0`

If you use a custom or local model and don't specify limits — and the model isn't in the built-in catalog — both `context` and `output` resolve to `0`. This has meaningful side effects:

- **Compaction is disabled.** Kilo uses `context` to detect when the conversation exceeds the model's window and needs to be summarized. With `context: 0`, overflow detection is skipped and conversations will grow unbounded until the provider rejects the request.
- **Output falls back to 32,000 tokens.** When `output` is `0`, Kilo uses its internal default of 32,000 tokens (configurable via the `KILO_EXPERIMENTAL_OUTPUT_TOKEN_MAX` environment variable).
- **No context usage tracking.** Usage metrics that depend on knowing the context size are skipped.

{% callout type="warning" %}
For custom and local models, always set `limit.context` and `limit.output` to match the model's actual capabilities. Without these values, automatic context management is disabled.
{% /callout %}

## Examples

### Local model with LM Studio

Register a model that LM Studio serves under a custom name:

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "lmstudio/deepseek-r1-0528",
  "provider": {
    "lmstudio": {
      "models": {
        "deepseek-r1-0528": {
          "name": "DeepSeek R1 0528",
        },
      },
    },
  },
}
```

### Local model with Ollama

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "ollama/my-finetune:latest",
  "provider": {
    "ollama": {
      "models": {
        "my-finetune:latest": {
          "name": "My Fine-tuned Model",
          "tool_call": true,
          "limit": {
            "context": 32768,
            "output": 8192,
          },
        },
      },
    },
  },
}
```

### New or unlisted model from a cloud provider

Use a model that's not yet in the built-in catalog:

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "openai/gpt-6-preview",
  "provider": {
    "openai": {
      "models": {
        "gpt-6-preview": {
          "name": "GPT-6 Preview",
          "tool_call": true,
          "reasoning": true,
          "limit": {
            "context": 200000,
            "output": 32768,
          },
        },
      },
    },
  },
}
```

### OpenAI-compatible provider with a custom endpoint

Connect to any provider that exposes an OpenAI-compatible API:

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "openai-compatible/my-model",
  "provider": {
    "openai-compatible": {
      "options": {
        "apiKey": "{env:MY_PROVIDER_API_KEY}",
        "baseURL": "https://api.my-provider.com/v1",
      },
      "models": {
        "my-model": {
          "name": "My Custom Model",
          "tool_call": true,
          "limit": {
            "context": 128000,
            "output": 16384,
          },
        },
      },
    },
  },
}
```

### Configuring model options and variants

Override options or define reasoning variants for a built-in model:

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "provider": {
    "anthropic": {
      "models": {
        "claude-sonnet-4-20250514": {
          "options": {
            "thinking": {
              "type": "enabled",
              "budgetTokens": 16000,
            },
          },
          "variants": {
            "thinking-high": {
              "thinking": {
                "type": "enabled",
                "budgetTokens": 32000,
              },
            },
            "fast": {
              "disabled": true,
            },
          },
        },
      },
    },
  },
}
```

### Using the id field to map model names

If the model key in your config differs from what the provider expects, use the `id` field:

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "lmstudio/my-local-llama",
  "provider": {
    "lmstudio": {
      "models": {
        "my-local-llama": {
          "id": "meta-llama-3.1-8b-instruct",
          "name": "Llama 3.1 8B (Local)",
        },
      },
    },
  },
}
```

Here `my-local-llama` is the key you use in your config and model picker, while `meta-llama-3.1-8b-instruct` is the actual model identifier sent to the LM Studio API.

For Azure OpenAI, use the native `azure` provider and set `id` to your Azure deployment name when it differs from the model key. Do not configure Azure GPT-5 family deployments under `openai-compatible`, because that provider sends `max_tokens` and Azure GPT-5 expects `max_completion_tokens`.

```jsonc
{
  "$schema": "https://app.kilo.ai/config.json",
  "model": "azure/gpt-5.5",
  "provider": {
    "azure": {
      "options": {
        "apiKey": "{env:AZURE_API_KEY}",
        "resourceName": "my-azure-resource",
      },
      "models": {
        "gpt-5.5": {
          "id": "my-gpt-5-5-deployment",
          "name": "GPT-5.5 on Azure",
          "reasoning": true,
          "tool_call": true,
          "temperature": false,
          "limit": {
            "context": 400000,
            "output": 128000,
          },
        },
      },
    },
  },
}
```

Here `azure/gpt-5.5` is the model you select in Kilo Code, while `my-gpt-5-5-deployment` is the Azure deployment name sent to Azure. If you prefer to configure the full Azure endpoint instead of a resource name, replace `resourceName` with `baseURL`, for example `"baseURL": "https://my-resource.openai.azure.com/openai"`. If both are configured, Kilo Code uses `baseURL` and ignores `resourceName` to avoid sending conflicting Azure SDK options.

## Model Loading Priority

When Kilo starts, it resolves the active model in this order:

1. The `--model` (or `-m`) command-line flag
2. The `model` key in your config file
3. The last used model from your previous session
4. The first available model using an internal priority

The format for all of these is `provider_id/model_id`.

## Provider-Level Options

You can also set options that apply to all models from a provider:

```jsonc
{
  "provider": {
    "openai": {
      "options": {
        "apiKey": "{env:OPENAI_API_KEY}",
        "baseURL": "https://my-proxy.example.com/v1",
        "timeout": 300000,
      },
    },
  },
}
```

| Option | Type | Description |
|---|---|---|
| `apiKey` | `string` | API key (supports `{env:VAR}` syntax) |
| `baseURL` | `string` | Override the provider's base API URL |
| `timeout` | `number \| false` | Request timeout in milliseconds. Defaults to `300000` (5 minutes); set to `false` to disable |

## Filtering Available Models

Control which models appear in the model picker for a provider using allowlists and blocklists:

```jsonc
{
  "provider": {
    "openai": {
      "whitelist": ["gpt-5", "gpt-5-mini"],
      "blacklist": ["gpt-4-turbo"],
    },
  },
}
```

- **`whitelist`** — only these model IDs are available from this provider
- **`blacklist`** — these model IDs are hidden from this provider

## Troubleshooting

**Model doesn't appear in the model picker:**

- Verify the provider has valid credentials configured (API key, or local server running)
- Check that the model key matches what you set in `"model": "provider/model-key"`
- Run `kilo models` to list all available models and confirm your provider is active

**Model errors or unexpected behavior:**

- Set `tool_call: true` if you need the model to use tools (file editing, terminal, etc.)
- Set `limit.context` and `limit.output` to match the model's actual capabilities — see [Token Limits](#token-limits-limit) above for details and defaults
- If conversations seem to grow without being compacted, your `limit.context` is likely `0` (unset)
- For local models, ensure your inference server is running and accessible at the configured URL
