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sync-2026-06-12
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main
| Author | SHA1 | Date | |
|---|---|---|---|
 The Librarian
|
1f556d946e | ||
|
The Librarian
|
6d510760b7 |
+2
-2
@@ -4,8 +4,8 @@ This is a mirror of the Ollama repository.
|
||||
|
||||
**Synced from:** https://github.com/ollama/ollama.git
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**Branch:** main
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**Commit:** 12e04379cd5a9a2f150104a02c5761213f4be777
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**Sync Date:** 2026-06-12
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**Commit:** 948f69330acf96a2310f1b53fdfc211731a386d8
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**Sync Date:** 2026-08-12
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**Content:** Paths: docs
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---
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+1
-1
@@ -19,5 +19,5 @@
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### Resources
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||||
|
||||
* [Troubleshooting Guide](https://docs.ollama.com/troubleshooting)
|
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* [FAQ](https://docs.ollama.com/faq#faq)
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* [FAQ](https://docs.ollama.com/faq)
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* [Development guide](./development.md)
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|
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+5
-65
@@ -16,7 +16,6 @@
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- [Generate Embeddings](#generate-embeddings)
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- [List Running Models](#list-running-models)
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- [Version](#version)
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- [Experimental: Image Generation](#image-generation-experimental)
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|
||||
## Conventions
|
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|
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@@ -46,7 +45,7 @@ Generate a response for a given prompt with a provided model. This is a streamin
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- `prompt`: the prompt to generate a response for
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- `suffix`: the text after the model response
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- `images`: (optional) a list of base64-encoded images (for multimodal models such as `llava`)
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- `think`: (for thinking models) should the model think before responding?
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- `think`: (for thinking models) should the model think before responding? Can be a boolean or a thinking level (`"low"`, `"medium"`, `"high"`, or `"max"`).
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|
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Advanced parameters (optional):
|
||||
|
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@@ -59,15 +58,6 @@ Advanced parameters (optional):
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- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
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- `context` (deprecated): the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
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|
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Experimental image generation parameters (for image generation models only):
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|
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> [!WARNING]
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> These parameters are experimental and may change in future versions.
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|
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- `width`: width of the generated image in pixels
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- `height`: height of the generated image in pixels
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- `steps`: number of diffusion steps
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|
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#### Structured outputs
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|
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Structured outputs are supported by providing a JSON schema in the `format` parameter. The model will generate a response that matches the schema. See the [structured outputs](#request-structured-outputs) example below.
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@@ -504,7 +494,7 @@ Generate the next message in a chat with a provided model. This is a streaming e
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- `model`: (required) the [model name](#model-names)
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- `messages`: the messages of the chat, this can be used to keep a chat memory
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- `tools`: list of tools in JSON for the model to use if supported
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- `think`: (for thinking models) should the model think before responding?
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- `think`: (for thinking models) should the model think before responding? Can be a boolean or a thinking level (`"low"`, `"medium"`, `"high"`, or `"max"`).
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|
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The `message` object has the following fields:
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|
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@@ -1189,7 +1179,7 @@ Create a model from:
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- a safetensors directory; or
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- a GGUF file.
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|
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If you are creating a model from a safetensors directory or from a GGUF file, you must [create a blob](#create-a-blob) for each of the files and then use the file name and SHA256 digest associated with each blob in the `files` field.
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If you are creating a model from a safetensors directory or from a GGUF file, you must [push a blob](#push-a-blob) for each of the files and then use the file name and SHA256 digest associated with each blob in the `files` field.
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|
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### Parameters
|
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|
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@@ -1198,6 +1188,8 @@ If you are creating a model from a safetensors directory or from a GGUF file, yo
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- `files`: (optional) a dictionary of file names to SHA256 digests of blobs to create the model from
|
||||
- `adapters`: (optional) a dictionary of file names to SHA256 digests of blobs for LORA adapters
|
||||
- `template`: (optional) the prompt template for the model
|
||||
- `renderer`: (optional) the name of the renderer for the model
|
||||
- `parser`: (optional) the name of the parser for the model
|
||||
- `license`: (optional) a string or list of strings containing the license or licenses for the model
|
||||
- `system`: (optional) a string containing the system prompt for the model
|
||||
- `parameters`: (optional) a dictionary of parameters for the model (see [Modelfile](./modelfile.mdx#valid-parameters-and-values) for a list of parameters)
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@@ -1878,55 +1870,3 @@ curl http://localhost:11434/api/version
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"version": "0.5.1"
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}
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```
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|
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## Experimental Features
|
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|
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### Image Generation (Experimental)
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> [!WARNING]
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> Image generation is experimental and may change in future versions.
|
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|
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Image generation is now supported through the standard `/api/generate` endpoint when using image generation models. The API automatically detects when an image generation model is being used.
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|
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See the [Generate a completion](#generate-a-completion) section for the full API documentation. The experimental image generation parameters (`width`, `height`, `steps`) are documented there.
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|
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#### Example
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|
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##### Request
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|
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```shell
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curl http://localhost:11434/api/generate -d '{
|
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"model": "x/z-image-turbo",
|
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"prompt": "a sunset over mountains",
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"width": 1024,
|
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"height": 768
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}'
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```
|
||||
|
||||
##### Response (streaming)
|
||||
|
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Progress updates during generation:
|
||||
|
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```json
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{
|
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"model": "x/z-image-turbo",
|
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"created_at": "2024-01-15T10:30:00.000000Z",
|
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"completed": 5,
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"total": 20,
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"done": false
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}
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```
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##### Final Response
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|
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```json
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{
|
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"model": "x/z-image-turbo",
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"created_at": "2024-01-15T10:30:15.000000Z",
|
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"image": "iVBORw0KGgoAAAANSUhEUg...",
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"done": true,
|
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"done_reason": "stop",
|
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"total_duration": 15000000000,
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"load_duration": 2000000000
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}
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```
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|
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@@ -2,11 +2,11 @@
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title: Introduction
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---
|
||||
|
||||
Ollama's API allows you to run and interact with models programatically.
|
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Use Ollama's API to run and interact with models.
|
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|
||||
## Get started
|
||||
|
||||
If you're just getting started, follow the [quickstart](/quickstart) documentation to get up and running with Ollama's API.
|
||||
Follow the [quickstart](/quickstart) to install Ollama and make your first request.
|
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|
||||
## Base URL
|
||||
|
||||
@@ -16,7 +16,7 @@ After installation, Ollama's API is served by default at:
|
||||
http://localhost:11434/api
|
||||
```
|
||||
|
||||
For running cloud models on **ollama.com**, the same API is available with the following base URL:
|
||||
For running cloud models on [ollama.com](https://ollama.com), the same API is available with the following base URL:
|
||||
|
||||
```
|
||||
https://ollama.com/api
|
||||
@@ -40,7 +40,7 @@ Ollama has official libraries for Python and JavaScript:
|
||||
- [Python](https://github.com/ollama/ollama-python)
|
||||
- [JavaScript](https://github.com/ollama/ollama-js)
|
||||
|
||||
Several community-maintained libraries are available for Ollama. For a full list, see the [Ollama GitHub repository](https://github.com/ollama/ollama?tab=readme-ov-file#libraries-1).
|
||||
Several community-maintained libraries are available for Ollama. For a full list, see the [Ollama GitHub repository](https://github.com/ollama/ollama?tab=readme-ov-file#libraries--sdks).
|
||||
|
||||
## Versioning
|
||||
|
||||
|
||||
@@ -208,9 +208,9 @@ curl -X POST http://localhost:11434/v1/chat/completions \
|
||||
- [x] `top_p`
|
||||
- [x] `max_tokens`
|
||||
- [x] `tools`
|
||||
- [x] `reasoning_effort` (`"high"`, `"medium"`, `"low"`, `"none"`)
|
||||
- [x] `reasoning_effort` (`"high"`, `"medium"`, `"low"`, `"max"`, `"none"`)
|
||||
- [x] `reasoning`
|
||||
- [x] `effort` (`"high"`, `"medium"`, `"low"`, `"none"`)
|
||||
- [x] `effort` (`"high"`, `"medium"`, `"low"`, `"max"`, `"none"`)
|
||||
- [ ] `tool_choice`
|
||||
- [ ] `logit_bias`
|
||||
- [ ] `user`
|
||||
@@ -279,73 +279,6 @@ curl -X POST http://localhost:11434/v1/chat/completions \
|
||||
- [x] `dimensions`
|
||||
- [ ] `user`
|
||||
|
||||
### `/v1/images/generations` (experimental)
|
||||
|
||||
> Note: This endpoint is experimental and may change or be removed in future versions.
|
||||
|
||||
Generate images using image generation models.
|
||||
|
||||
<CodeGroup dropdown>
|
||||
|
||||
```python images.py
|
||||
from openai import OpenAI
|
||||
|
||||
client = OpenAI(
|
||||
base_url='http://localhost:11434/v1/',
|
||||
api_key='ollama', # required but ignored
|
||||
)
|
||||
|
||||
response = client.images.generate(
|
||||
model='x/z-image-turbo',
|
||||
prompt='A cute robot learning to paint',
|
||||
size='1024x1024',
|
||||
response_format='b64_json',
|
||||
)
|
||||
print(response.data[0].b64_json[:50] + '...')
|
||||
```
|
||||
|
||||
```javascript images.js
|
||||
import OpenAI from "openai";
|
||||
|
||||
const openai = new OpenAI({
|
||||
baseURL: "http://localhost:11434/v1/",
|
||||
apiKey: "ollama", // required but ignored
|
||||
});
|
||||
|
||||
const response = await openai.images.generate({
|
||||
model: "x/z-image-turbo",
|
||||
prompt: "A cute robot learning to paint",
|
||||
size: "1024x1024",
|
||||
response_format: "b64_json",
|
||||
});
|
||||
|
||||
console.log(response.data[0].b64_json.slice(0, 50) + "...");
|
||||
```
|
||||
|
||||
```shell images.sh
|
||||
curl -X POST http://localhost:11434/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"model": "x/z-image-turbo",
|
||||
"prompt": "A cute robot learning to paint",
|
||||
"size": "1024x1024",
|
||||
"response_format": "b64_json"
|
||||
}'
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
#### Supported request fields
|
||||
|
||||
- [x] `model`
|
||||
- [x] `prompt`
|
||||
- [x] `size` (e.g. "1024x1024")
|
||||
- [x] `response_format` (only `b64_json` supported)
|
||||
- [ ] `n`
|
||||
- [ ] `quality`
|
||||
- [ ] `style`
|
||||
- [ ] `user`
|
||||
|
||||
### `/v1/responses`
|
||||
|
||||
> Note: Added in Ollama v0.13.3
|
||||
|
||||
@@ -16,9 +16,9 @@ Use this capability to audit model steps, animate the model *thinking* in a UI,
|
||||
|
||||
## Enable thinking in API calls
|
||||
|
||||
Set the `think` field on chat or generate requests. Most models accept booleans (`true`/`false`).
|
||||
Set the `think` field on chat or generate requests. Most models accept booleans (`true`/`false`) or levels (`low`, `medium`, `high`, `max`), where `max` requests the highest thinking level.
|
||||
|
||||
GPT-OSS instead expects one of `low`, `medium`, or `high` to tune the trace length.
|
||||
GPT-OSS instead expects one of `low`, `medium`, or `high` to tune the trace length.
|
||||
|
||||
The `message.thinking` (chat endpoint) or `thinking` (generate endpoint) field contains the reasoning trace while `message.content` / `response` holds the final answer.
|
||||
|
||||
|
||||
+49
-11
@@ -229,9 +229,9 @@ curl https://ollama.com/api/chat \
|
||||
|
||||
## Local only
|
||||
|
||||
Ollama can run in local-only mode by [disabling Ollama's cloud](./faq#how-do-i-disable-ollama-cloud) features.
|
||||
Ollama can run in local-only mode by [disabling Ollama's cloud](./faq#how-do-i-disable-ollama-cloud-features) features.
|
||||
|
||||
## Deprecations
|
||||
## Retirements
|
||||
|
||||
Ollama will occasionally deprecate and retire older cloud models as newer and better open-source models are released.
|
||||
Tools and applications relying on Ollama Cloud models may need to be updated to keep working. Impacted users will be
|
||||
@@ -240,15 +240,53 @@ Ollama website.
|
||||
|
||||
Ollama Cloud model retirement does not affect local models.
|
||||
|
||||
### Upcoming deprecations
|
||||
### Upcoming retirements
|
||||
|
||||
| Retirement date | Model | Recommended alternative |
|
||||
| --- | --- | --- |
|
||||
| June 16, 2026 | `kimi-k2-thinking` | `kimi-k2.6` |
|
||||
| June 16, 2026 | `kimi-k2:1t` | `kimi-k2.6` |
|
||||
| June 16, 2026 | `minimax-m2` | `minimax-m3` |
|
||||
| June 16, 2026 | `glm-4.6` | `glm-5.1` |
|
||||
| June 16, 2026 | `qwen3-next:80b` | `qwen3.5` |
|
||||
| June 16, 2026 | `qwen3-vl:235b` | `qwen3.5` |
|
||||
| June 16, 2026 | `qwen3-vl:235b-instruct` | `qwen3.5` |
|
||||
| June 16, 2026 | `cogito-2.1:671b` | `deepseek-v4-flash` |
|
||||
| July 31, 2026 | `minimax-m2.5` | `minimax-m2.7` |
|
||||
| July 31, 2026 | `kimi-k2.5` | `kimi-k2.6` |
|
||||
|
||||
### Past retirements
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="July 15, 2026">
|
||||
| Model | Recommended alternative |
|
||||
| --- | --- |
|
||||
| `deepseek-v3.1:671b` | `deepseek-v4-flash` |
|
||||
| `deepseek-v3.2` | `deepseek-v4-flash` |
|
||||
| `devstral-2:123b` | `mistral-large-3:675b` |
|
||||
| `devstral-small-2:24b` | |
|
||||
| `ministral-3:14b` | |
|
||||
| `ministral-3:3b` | |
|
||||
| `ministral-3:8b` | |
|
||||
| `gemini-3-flash-preview` | `minimax-m3` |
|
||||
| `gemma3:12b` | `gemma4:31b` |
|
||||
| `gemma3:27b` | `gemma4:31b` |
|
||||
| `gemma3:4b` | `gemma4:31b` |
|
||||
| `glm-4.7` | `glm-5.2` |
|
||||
| `glm-5` | `glm-5.2` |
|
||||
| `minimax-m2.1` | `minimax-m3` |
|
||||
| `qwen3-coder-next` | `qwen3.5:397b` |
|
||||
| `qwen3-coder:480b` | `qwen3.5:397b` |
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="June 30, 2026">
|
||||
| Model | Recommended alternative |
|
||||
| --- | --- |
|
||||
| `rnj-1:8b` | |
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="June 16, 2026">
|
||||
| Model | Recommended alternative |
|
||||
| --- | --- |
|
||||
| `kimi-k2-thinking` | `kimi-k2.6` |
|
||||
| `kimi-k2:1t` | `kimi-k2.6` |
|
||||
| `minimax-m2` | `minimax-m3` |
|
||||
| `glm-4.6` | `glm-5.1` |
|
||||
| `qwen3-next:80b` | `qwen3.5` |
|
||||
| `qwen3-vl:235b` | `qwen3.5` |
|
||||
| `qwen3-vl:235b-instruct` | `qwen3.5` |
|
||||
| `cogito-2.1:671b` | `deepseek-v4-flash` |
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
+2
-2
@@ -51,10 +51,10 @@ cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=nat
|
||||
cmake -B build . -DOLLAMA_LLAMA_BACKENDS=rocm_v7_2 -DCMAKE_HIP_ARCHITECTURES=gfx1100
|
||||
```
|
||||
|
||||
You can tune GGML build options by setting `GGML_*` values during configure. For example, to build CUDA v12 for Pascal without flash attention kernels:
|
||||
You can tune GGML build options by setting `GGML_*` values during configure. For example, to disable CUDA flash attention kernels for local debugging:
|
||||
|
||||
```shell
|
||||
cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v12 -DCMAKE_CUDA_ARCHITECTURES=61 -DGGML_CUDA_FA=OFF
|
||||
cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v12 -DGGML_CUDA_FA=OFF
|
||||
```
|
||||
|
||||
## macOS (Apple Silicon)
|
||||
|
||||
+94
-69
@@ -60,6 +60,26 @@
|
||||
}
|
||||
},
|
||||
"redirects": [
|
||||
{
|
||||
"source": "/development.md",
|
||||
"destination": "/development"
|
||||
},
|
||||
{
|
||||
"source": "/api/openai-compatibility.mdx",
|
||||
"destination": "/api/openai-compatibility"
|
||||
},
|
||||
{
|
||||
"source": "/gpu.mdx",
|
||||
"destination": "/gpu"
|
||||
},
|
||||
{
|
||||
"source": "/integrations/vscode.mdx",
|
||||
"destination": "/integrations/vscode"
|
||||
},
|
||||
{
|
||||
"source": "/troubleshooting.mdx",
|
||||
"destination": "/troubleshooting"
|
||||
},
|
||||
{
|
||||
"source": "/openai",
|
||||
"destination": "/api/openai-compatibility"
|
||||
@@ -84,7 +104,7 @@
|
||||
"navigation": {
|
||||
"tabs": [
|
||||
{
|
||||
"tab": "Documentation",
|
||||
"tab": "Guide",
|
||||
"groups": [
|
||||
{
|
||||
"group": "Get started",
|
||||
@@ -106,78 +126,10 @@
|
||||
"/capabilities/web-search"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Integrations",
|
||||
"pages": [
|
||||
"/integrations/index",
|
||||
{
|
||||
"group": "Assistants",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/openclaw",
|
||||
"/integrations/hermes",
|
||||
"/integrations/hermes-desktop"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Coding",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/claude-code",
|
||||
"/integrations/codex-app",
|
||||
"/integrations/codex",
|
||||
"/integrations/copilot-cli",
|
||||
"/integrations/cline-cli",
|
||||
"/integrations/opencode",
|
||||
"/integrations/droid",
|
||||
"/integrations/goose",
|
||||
"/integrations/oh-my-pi",
|
||||
"/integrations/pi",
|
||||
"/integrations/pool"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "IDEs & Editors",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/cline",
|
||||
"/integrations/jetbrains",
|
||||
"/integrations/roo-code",
|
||||
"/integrations/vscode",
|
||||
"/integrations/xcode",
|
||||
"/integrations/zed"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Chat & RAG",
|
||||
"pages": [
|
||||
"/integrations/onyx"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Automation",
|
||||
"pages": [
|
||||
"/integrations/n8n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Notebooks",
|
||||
"pages": [
|
||||
"/integrations/marimo"
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "More information",
|
||||
"pages": [
|
||||
"/cli",
|
||||
{
|
||||
"group": "Assistant Sandboxing",
|
||||
"pages": [
|
||||
"/integrations/nemoclaw"
|
||||
]
|
||||
},
|
||||
"/modelfile",
|
||||
"/context-length",
|
||||
"/linux",
|
||||
@@ -192,6 +144,79 @@
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"tab": "Integrations",
|
||||
"groups": [
|
||||
{
|
||||
"group": "Integrations",
|
||||
"pages": [
|
||||
"/integrations/index"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Assistants",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/openclaw",
|
||||
"/integrations/hermes",
|
||||
"/integrations/hermes-desktop"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Coding",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/claude-code",
|
||||
"/integrations/opencode",
|
||||
"/integrations/cline-cli",
|
||||
"/integrations/codex-app",
|
||||
"/integrations/codex",
|
||||
"/integrations/copilot-cli",
|
||||
"/integrations/droid",
|
||||
"/integrations/goose",
|
||||
"/integrations/oh-my-pi",
|
||||
"/integrations/pi",
|
||||
"/integrations/pool"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "IDEs & Editors",
|
||||
"expanded": true,
|
||||
"pages": [
|
||||
"/integrations/vscode",
|
||||
"/integrations/cline",
|
||||
"/integrations/jetbrains",
|
||||
"/integrations/roo-code",
|
||||
"/integrations/xcode",
|
||||
"/integrations/zed"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Chat & RAG",
|
||||
"pages": [
|
||||
"/integrations/onyx"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Automation",
|
||||
"pages": [
|
||||
"/integrations/n8n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Notebooks",
|
||||
"pages": [
|
||||
"/integrations/marimo"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Assistant Sandboxing",
|
||||
"pages": [
|
||||
"/integrations/nemoclaw"
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"tab": "API Reference",
|
||||
"openapi": "/openapi.yaml",
|
||||
|
||||
+1
-1
@@ -11,4 +11,4 @@ Ollama JavaScript examples at [ollama-js/examples](https://github.com/ollama/oll
|
||||
|
||||
|
||||
## OpenAI compatibility examples
|
||||
Ollama OpenAI compatibility examples at [ollama/examples/openai](../docs/openai.md)
|
||||
Ollama OpenAI compatibility examples at [ollama/examples/openai](./api/openai-compatibility.mdx)
|
||||
|
||||
+3
-3
@@ -160,7 +160,7 @@ docker run -d -e HTTPS_PROXY=https://my.proxy.example.com -p 11434:11434 ollama-
|
||||
|
||||
Ollama runs locally. We don't see your prompts or data when you run locally. When using cloud-hosted models, we process your prompts and responses to provide the service but do not store or log that content and never train on it. We collect basic account info and limited usage metadata to provide the service that does not include prompt or response content. We don't sell your data. You can delete your account anytime.
|
||||
|
||||
## How do I disable Ollama's cloud features?
|
||||
## How do I disable Ollama Cloud features?
|
||||
|
||||
Ollama can run in local only mode by disabling Ollama's cloud features. By turning off Ollama's cloud features, you will lose the ability to use Ollama's cloud models and web search.
|
||||
|
||||
@@ -248,7 +248,7 @@ Refer to the section [above](#how-do-i-configure-ollama-server) for how to set e
|
||||
|
||||
## How can I use Ollama in Visual Studio Code?
|
||||
|
||||
There is already a large collection of plugins available for VS Code as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/ollama/ollama#extensions--plugins) at the bottom of the main repository readme.
|
||||
Install the [Ollama extension](https://marketplace.visualstudio.com/items?itemName=Ollama.ollama) to use Ollama models in VS Code Chat. See the [VS Code integration guide](./integrations/vscode.mdx) for setup and troubleshooting.
|
||||
|
||||
## How do I use Ollama with GPU acceleration in Docker?
|
||||
|
||||
@@ -343,7 +343,7 @@ When loading a new model, Ollama evaluates the required VRAM for the model again
|
||||
|
||||
## How can I enable Flash Attention?
|
||||
|
||||
Flash Attention is a feature of most modern models that can significantly reduce memory usage as the context size grows. To enable Flash Attention, set the `OLLAMA_FLASH_ATTENTION` environment variable to `1` when starting the Ollama server.
|
||||
Flash Attention is a feature of most modern models that can significantly reduce memory usage as the context size grows. Ollama uses Flash Attention automatically when the selected backend and devices support it. To force Flash Attention on, set `OLLAMA_FLASH_ATTENTION=1` when starting the Ollama server. To disable it, set `OLLAMA_FLASH_ATTENTION=0`.
|
||||
|
||||
## How can I set the quantization type for the K/V cache?
|
||||
|
||||
|
||||
+5
-8
@@ -3,7 +3,7 @@ title: Hardware support
|
||||
---
|
||||
|
||||
## Nvidia
|
||||
Ollama supports Nvidia GPUs with compute capability 5.0+ and driver version 531 and newer.
|
||||
Ollama supports Nvidia GPUs with compute capability 5.0+ and driver version 550 and newer.
|
||||
Nvidia GPUs with compute capability 5.0 through 6.2 require driver version 570 or newer.
|
||||
|
||||
Check your compute compatibility to see if your card is supported:
|
||||
@@ -35,7 +35,7 @@ Check your compute compatibility to see if your card is supported:
|
||||
| 5.0 | GeForce GTX | `GTX 750 Ti` `GTX 750` `NVS 810` |
|
||||
| | Quadro | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M` |
|
||||
|
||||
For building locally to support older GPUs, see [developer](./development#linux-cuda-nvidia)
|
||||
For building locally to support older GPUs, see [development](./development.md).
|
||||
|
||||
### GPU Selection
|
||||
|
||||
@@ -68,7 +68,7 @@ using the `amdgpu-install` utility from
|
||||
|
||||
| Family | Cards and accelerators |
|
||||
| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| AMD Radeon RX | `9070 XT` `9070 GRE` `9070` `9060 XT` `9060 XT LP` `9060` `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7700` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `5700 XT` `5700` `5600 XT` `5500 XT` |
|
||||
| AMD Radeon RX | `9070 XT` `9070 GRE` `9070` `9060 XT` `9060 XT LP` `9060` `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7700` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` |
|
||||
| AMD Radeon AI PRO | `R9700` `R9600D` |
|
||||
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` |
|
||||
| AMD Ryzen AI | `Ryzen AI Max+ 395` `Ryzen AI Max 390` `Ryzen AI Max 385` `Ryzen AI 9 HX 475` `Ryzen AI 9 HX 470` `Ryzen AI 9 465` `Ryzen AI 9 HX 375` `Ryzen AI 9 HX 370` `Ryzen AI 9 365` |
|
||||
@@ -80,8 +80,8 @@ Ollama requires an AMD ROCm v7 / HIP7-capable driver stack on Windows.
|
||||
|
||||
| Family | Cards and accelerators |
|
||||
| -------------- | -------------------------------------------------------------------------------------------------------------------- |
|
||||
| AMD Radeon RX | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` |
|
||||
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` |
|
||||
| AMD Radeon RX | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` |
|
||||
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` |
|
||||
|
||||
### Overrides on Linux
|
||||
|
||||
@@ -107,13 +107,10 @@ This table shows some example GPUs that map to these LLVM targets:
|
||||
| gfx90a | Radeon Instinct MI210/MI250 |
|
||||
| gfx942 | Radeon Instinct MI300X/MI300A |
|
||||
| gfx950 | Radeon Instinct MI350X |
|
||||
| gfx1010 | Radeon RX 5700 XT |
|
||||
| gfx1012 | Radeon RX 5500 XT |
|
||||
| gfx1030 | Radeon PRO V620 |
|
||||
| gfx1100 | Radeon PRO W7900 |
|
||||
| gfx1101 | Radeon PRO W7700 |
|
||||
| gfx1102 | Radeon RX 7600 |
|
||||
| gfx1103 | Radeon 780M |
|
||||
| gfx1150 | Ryzen AI 9 HX 375 |
|
||||
| gfx1151 | Ryzen AI Max+ 395 |
|
||||
| gfx1200 | Radeon RX 9070 |
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
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After Width: | Height: | Size: 3.4 KiB |
+4
-4
@@ -4,10 +4,10 @@ title: Importing a Model
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Importing a Safetensors adapter](#Importing-a-fine-tuned-adapter-from-Safetensors-weights)
|
||||
- [Importing a Safetensors model](#Importing-a-model-from-Safetensors-weights)
|
||||
- [Importing a GGUF file](#Importing-a-GGUF-based-model-or-adapter)
|
||||
- [Sharing models on ollama.com](#Sharing-your-model-on-ollamacom)
|
||||
- [Importing a Safetensors adapter](#importing-a-fine-tuned-adapter-from-safetensors-weights)
|
||||
- [Importing a Safetensors model](#importing-a-model-from-safetensors-weights)
|
||||
- [Importing a GGUF file](#importing-a-gguf-based-model-or-adapter)
|
||||
- [Sharing models on ollama.com](#sharing-your-model-on-ollama-com)
|
||||
|
||||
## Importing a fine tuned adapter from Safetensors weights
|
||||
|
||||
|
||||
+28
-30
@@ -1,47 +1,45 @@
|
||||
---
|
||||
title: Ollama's documentation
|
||||
title: Ollama documentation
|
||||
sidebarTitle: Welcome
|
||||
---
|
||||
|
||||
<img src="/images/welcome.png" noZoom className="rounded-3xl" />
|
||||
Start building with open models.
|
||||
|
||||
[Ollama](https://ollama.com) is the easiest way to get up and running with large language models such as gpt-oss, Gemma 4, DeepSeek-R1, Qwen3 and more.
|
||||
Follow the [quickstart](/quickstart), then choose a model, integration, or API.
|
||||
|
||||
## Models
|
||||
|
||||
Run models locally or use larger models in Ollama's cloud.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Quickstart" icon="rocket" href="/quickstart">
|
||||
Get up and running with your first model or integrate Ollama with your favorite tools
|
||||
<Card title="Browse models" icon="star" href="https://ollama.com/search">
|
||||
Find models for chat, coding, vision, embeddings, and reasoning.
|
||||
</Card>
|
||||
<Card
|
||||
title="Download Ollama"
|
||||
icon="download"
|
||||
href="https://ollama.com/download"
|
||||
>
|
||||
Download Ollama on macOS, Windows or Linux
|
||||
</Card>
|
||||
<Card title="Cloud" icon="cloud" href="/cloud">
|
||||
Ollama's cloud models offer larger models with better performance.
|
||||
</Card>
|
||||
<Card title="API reference" icon="terminal" href="/api">
|
||||
View Ollama's API reference
|
||||
|
||||
<Card title="Cloud models" icon="cloud" href="/cloud">
|
||||
Run larger models on Ollama's Cloud without the download.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Libraries
|
||||
## Next steps
|
||||
|
||||
Connect Ollama to an app, or build with the API.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card
|
||||
title="Ollama's Python Library"
|
||||
icon="python"
|
||||
href="https://github.com/ollama/ollama-python"
|
||||
>
|
||||
The official library for using Ollama with Python
|
||||
<Card title="Integrations" icon="plug" href="/integrations">
|
||||
Connect Ollama to an app, editor, or agent.
|
||||
</Card>
|
||||
|
||||
<Card title="Ollama's JavaScript library" icon="js" href="https://github.com/ollama/ollama-js">
|
||||
The official library for using Ollama with JavaScript or TypeScript.
|
||||
<Card title="First API request" icon="code" href="/api/introduction">
|
||||
Learn the local and cloud base URLs, then send a request with `curl`.
|
||||
</Card>
|
||||
<Card title="Community libraries" icon="github" href="https://github.com/ollama/ollama?tab=readme-ov-file#libraries-1">
|
||||
View a list of 20+ community-supported libraries for Ollama
|
||||
|
||||
<Card title="Python library" icon="python" href="https://github.com/ollama/ollama-python">
|
||||
Use Ollama from Python.
|
||||
</Card>
|
||||
|
||||
<Card title="JavaScript library" icon="js" href="https://github.com/ollama/ollama-js">
|
||||
Use Ollama from JavaScript or TypeScript.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
@@ -49,10 +47,10 @@ sidebarTitle: Welcome
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Discord" icon="discord" href="https://discord.gg/ollama">
|
||||
Join our Discord community
|
||||
Join the Ollama Discord.
|
||||
</Card>
|
||||
|
||||
<Card title="Reddit" icon="reddit" href="https://reddit.com/r/ollama">
|
||||
Join our Reddit community
|
||||
Join the Ollama subreddit.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
@@ -2,15 +2,162 @@
|
||||
title: Claude Code
|
||||
---
|
||||
|
||||
Claude Code is Anthropic's agentic coding tool that can read, modify, and execute code in your working directory.
|
||||
[Claude Code](https://code.claude.com/docs/en/overview) is an agentic coding tool that reads your codebase, edits files, and runs commands.
|
||||
|
||||
Open models can be used with Claude Code through Ollama's Anthropic-compatible API, enabling you to use models such as `qwen3.5`, `glm-5:cloud`, `kimi-k2.5:cloud`.
|
||||
Ollama connects Claude Code to local and cloud models through its Anthropic-compatible API.
|
||||
|
||||
|
||||
## Get started
|
||||
|
||||
## Install
|
||||
Launch Claude Code with Ollama:
|
||||
|
||||
Install [Claude Code](https://code.claude.com/docs/en/overview):
|
||||
```shell
|
||||
ollama launch claude
|
||||
```
|
||||
|
||||
## Capabilities
|
||||
|
||||
<div className="capability-list capability-list-full">
|
||||
<div className="capability-list-grid">
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="comment" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Chat</div>
|
||||
<div className="capability-list-copy">Ask questions about a repository or task</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="terminal" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Command line</div>
|
||||
<div className="capability-list-copy">Run commands with Claude Code's permission flow</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="code" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Tool calling</div>
|
||||
<div className="capability-list-copy">Use tools with compatible models</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="file-pen" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">File edits</div>
|
||||
<div className="capability-list-copy">Read and edit files in your project</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="users" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Subagents</div>
|
||||
<div className="capability-list-copy">Split work across tasks</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="globe" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Web search</div>
|
||||
<div className="capability-list-copy">Search the web through Ollama</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="file-text" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Web fetch</div>
|
||||
<div className="capability-list-copy">Fetch and summarize web pages</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="image" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Vision</div>
|
||||
<div className="capability-list-copy">Send images and screenshots</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="brain" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Thinking</div>
|
||||
<div className="capability-list-copy">Use thinking controls with compatible models</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
## Models
|
||||
|
||||
Choose a model with enough context for your repository.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Cloud models" icon="cloud" href="https://ollama.com/search?c=cloud">
|
||||
Use larger models without downloading them.
|
||||
</Card>
|
||||
|
||||
<Card title="Local models" icon="hard-drive" href="https://ollama.com/search?c=tools">
|
||||
Choose a model and set a 64k+ context window.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
<Note>For larger repositories, set the [context length](/context-length) to 64k or higher.</Note>
|
||||
|
||||
## More features
|
||||
|
||||
### Run without interaction
|
||||
|
||||
Use `--yes` for scripts, Docker, or CI:
|
||||
|
||||
```shell
|
||||
ollama launch claude --model gemma4:cloud --yes -- -p "how does this repository work?"
|
||||
```
|
||||
|
||||
The `--yes` flag skips selectors, pulls the model when needed, and requires `--model`. Arguments after `--` are passed directly to Claude Code.
|
||||
|
||||
### Web search
|
||||
|
||||
Use Ollama's web search API from Claude Code.
|
||||
|
||||
See [Web search](/capabilities/web-search) for setup and usage.
|
||||
|
||||
### Scheduled tasks with `/loop`
|
||||
|
||||
Use `/loop` inside Claude Code to run a prompt or slash command on a schedule:
|
||||
|
||||
```text
|
||||
/loop <interval> <prompt or /command>
|
||||
```
|
||||
|
||||
Examples:
|
||||
|
||||
```text
|
||||
/loop 30m Check my open PRs and summarize their status
|
||||
/loop 1h Research the latest AI news and summarize key developments
|
||||
/loop 15m Check for new GitHub issues and triage by priority
|
||||
```
|
||||
|
||||
### Telegram
|
||||
|
||||
Connect a Telegram bot to your Claude Code session. Install the [Telegram plugin](https://github.com/anthropics/claude-plugins-official), create a bot with [@BotFather](https://t.me/BotFather), then launch Claude Code:
|
||||
|
||||
```shell
|
||||
ollama launch claude -- --channels plugin:telegram@claude-plugins-official
|
||||
```
|
||||
|
||||
Claude Code prompts for permission on most actions. To allow the bot to work autonomously, configure [permission rules](https://code.claude.com/docs/en/permissions) or pass `--dangerously-skip-permissions` in an isolated environment.
|
||||
|
||||
See the [plugin README](https://github.com/anthropics/claude-plugins-official/tree/main/external_plugins/telegram) for setup instructions.
|
||||
|
||||
## Manual setup
|
||||
|
||||
<p className="manual-step-title">1. Install Claude Code</p>
|
||||
|
||||
<CodeGroup>
|
||||
|
||||
@@ -24,95 +171,7 @@ irm https://claude.ai/install.ps1 | iex
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
## Usage with Ollama
|
||||
|
||||
### Quick setup
|
||||
|
||||
```shell
|
||||
ollama launch claude
|
||||
```
|
||||
|
||||
### Run directly with a model
|
||||
```shell
|
||||
ollama launch claude --model kimi-k2.5:cloud
|
||||
```
|
||||
|
||||
## Recommended Models
|
||||
|
||||
- `kimi-k2.5:cloud`
|
||||
- `glm-5:cloud`
|
||||
- `minimax-m2.7:cloud`
|
||||
- `qwen3.5:cloud`
|
||||
- `glm-4.7-flash`
|
||||
- `qwen3.5`
|
||||
|
||||
Cloud models are also available at [ollama.com/search?c=cloud](https://ollama.com/search?c=cloud).
|
||||
|
||||
## Non-interactive (headless) mode
|
||||
|
||||
Run Claude Code without interaction for use in Docker, CI/CD, or scripts:
|
||||
|
||||
```shell
|
||||
ollama launch claude --model kimi-k2.5:cloud --yes -- -p "how does this repository work?"
|
||||
```
|
||||
|
||||
The `--yes` flag auto-pulls the model, skips selectors, and requires `--model` to be specified. Arguments after `--` are passed directly to Claude Code.
|
||||
|
||||
## Web search
|
||||
|
||||
Claude Code can search the web through Ollama's web search API. See the [web search documentation](/capabilities/web-search) for setup and usage.
|
||||
|
||||
## Scheduled Tasks with `/loop`
|
||||
|
||||
The `/loop` command runs a prompt or slash command on a recurring schedule inside Claude Code. This is useful for automating repetitive tasks like checking PRs, running research, or setting reminders.
|
||||
|
||||
```
|
||||
/loop <interval> <prompt or /command>
|
||||
```
|
||||
|
||||
### Examples
|
||||
|
||||
**Check in on your PRs**
|
||||
|
||||
```
|
||||
/loop 30m Check my open PRs and summarize their status
|
||||
```
|
||||
|
||||
**Automate research tasks**
|
||||
|
||||
```
|
||||
/loop 1h Research the latest AI news and summarize key developments
|
||||
```
|
||||
|
||||
**Automate bug reporting and triaging**
|
||||
|
||||
```
|
||||
/loop 15m Check for new GitHub issues and triage by priority
|
||||
```
|
||||
|
||||
**Set reminders**
|
||||
|
||||
```
|
||||
/loop 1h Remind me to review the deploy status
|
||||
```
|
||||
|
||||
## Telegram
|
||||
|
||||
Chat with Claude Code from Telegram by connecting a bot to your session. Install the [Telegram plugin](https://github.com/anthropics/claude-plugins-official), create a bot via [@BotFather](https://t.me/BotFather), then launch with the channel flag:
|
||||
|
||||
```shell
|
||||
ollama launch claude -- --channels plugin:telegram@claude-plugins-official
|
||||
```
|
||||
|
||||
Claude Code will prompt for permission on most actions. To allow the bot to work autonomously, configure [permission rules](https://code.claude.com/docs/en/permissions) or pass `--dangerously-skip-permissions` in isolated environments.
|
||||
|
||||
See the [plugin README](https://github.com/anthropics/claude-plugins-official/tree/main/external_plugins/telegram) for full setup instructions including pairing and access control.
|
||||
|
||||
## Manual setup
|
||||
|
||||
Claude Code connects to Ollama using the Anthropic-compatible API.
|
||||
|
||||
1. Set the environment variables:
|
||||
<p className="manual-step-title">2. Set the environment variables</p>
|
||||
|
||||
```shell
|
||||
export ANTHROPIC_AUTH_TOKEN=ollama
|
||||
@@ -120,7 +179,7 @@ export ANTHROPIC_API_KEY=""
|
||||
export ANTHROPIC_BASE_URL=http://localhost:11434
|
||||
```
|
||||
|
||||
2. Run Claude Code with an Ollama model:
|
||||
<p className="manual-step-title">3. Run Claude Code</p>
|
||||
|
||||
```shell
|
||||
claude --model qwen3.5
|
||||
@@ -129,8 +188,5 @@ claude --model qwen3.5
|
||||
Or run with environment variables inline:
|
||||
|
||||
```shell
|
||||
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model glm-5:cloud
|
||||
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY="" claude --model kimi-k2.7-code:cloud
|
||||
```
|
||||
|
||||
**Note:** Claude Code requires a large context window. We recommend at least 64k tokens. See the [context length documentation](/context-length) for how to adjust context length in Ollama.
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ title: Goose
|
||||
|
||||
## Goose Desktop
|
||||
|
||||
Install [Goose](https://block.github.io/goose/docs/getting-started/installation/) Desktop.
|
||||
Install [Goose](https://goose-docs.ai/docs/getting-started/installation/) Desktop.
|
||||
|
||||
### Usage with Ollama
|
||||
1. In Goose, open **Settings** → **Configure Provider**.
|
||||
@@ -27,7 +27,7 @@ Install [Goose](https://block.github.io/goose/docs/getting-started/installation/
|
||||
|
||||
## Goose CLI
|
||||
|
||||
Install [Goose](https://block.github.io/goose/docs/getting-started/installation/) CLI
|
||||
Install [Goose](https://goose-docs.ai/docs/getting-started/installation/) CLI
|
||||
|
||||
### Usage with Ollama
|
||||
1. Run `goose configure`
|
||||
|
||||
@@ -14,7 +14,7 @@ ollama launch hermes-desktop
|
||||
|
||||
Ollama handles the setup flow automatically:
|
||||
|
||||
1. **Install** - If Hermes Desktop isn't installed, Ollama prompts to install it
|
||||
1. **Install** - If Hermes isn't installed, Ollama prompts to install the Hermes command-line agent. On first desktop launch, Hermes builds its packaged desktop app.
|
||||
2. **Model** - Pick a model from the selector
|
||||
3. **Configure** - Ollama configures Hermes Desktop to use your selected Ollama model
|
||||
4. **Launch** - Ollama opens Hermes Desktop
|
||||
@@ -26,3 +26,13 @@ ollama launch hermes-desktop --model <model>
|
||||
```
|
||||
|
||||
Run `ollama launch hermes-desktop` again to switch models later.
|
||||
|
||||
## Install Hermes Desktop directly
|
||||
|
||||
On macOS and Windows, the Hermes Desktop installer is the recommended upstream installation path. It installs the desktop app and Hermes Agent together. If you prefer the command line, `ollama launch hermes-desktop` remains the explicit Ollama-managed path and uses the same Hermes configuration, sessions, skills, and memory as the CLI.
|
||||
|
||||
To force Hermes to rebuild its packaged desktop app:
|
||||
|
||||
```bash
|
||||
ollama launch hermes-desktop -- --force-build
|
||||
```
|
||||
|
||||
@@ -14,7 +14,7 @@ ollama launch hermes
|
||||
|
||||
Ollama handles everything automatically:
|
||||
|
||||
1. **Install** — If Hermes isn't installed, Ollama prompts to install it via the Nous Research install script
|
||||
1. **Install** — If Hermes isn't installed, Ollama prompts to install the Hermes command-line agent
|
||||
2. **Model** — Pick a model from the selector (local or cloud)
|
||||
3. **Onboarding** — Ollama configures the Ollama provider, points Hermes at `http://127.0.0.1:11434/v1`, and sets your model as the primary
|
||||
4. **Gateway** — Optionally connects a messaging platform (Telegram, Discord, Slack, WhatsApp, Signal, Email) and launches the Hermes chat
|
||||
@@ -45,10 +45,10 @@ hermes gateway setup
|
||||
|
||||
## Reconfigure
|
||||
|
||||
Re-run the full setup wizard at any time:
|
||||
Use Hermes's model picker to change providers or models later:
|
||||
|
||||
```bash
|
||||
hermes setup
|
||||
hermes model
|
||||
```
|
||||
|
||||
## Manual setup
|
||||
@@ -56,7 +56,7 @@ hermes setup
|
||||
If you'd rather drive Hermes's own wizard instead of `ollama launch hermes`, install it directly:
|
||||
|
||||
```bash
|
||||
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
|
||||
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
|
||||
```
|
||||
|
||||
Hermes launches the setup wizard automatically. Choose **Quick setup**:
|
||||
@@ -106,7 +106,7 @@ Optionally connect a messaging platform during setup:
|
||||
Connect a messaging platform? (Telegram, Discord, etc.)
|
||||
|
||||
→ Set up messaging now (recommended)
|
||||
Skip — set up later with 'hermes setup gateway'
|
||||
Skip — set up later with 'hermes gateway setup'
|
||||
```
|
||||
|
||||
### Launch
|
||||
@@ -114,4 +114,3 @@ Connect a messaging platform? (Telegram, Discord, etc.)
|
||||
```
|
||||
Launch hermes chat now? [Y/n]: Y
|
||||
```
|
||||
|
||||
|
||||
+28
-42
@@ -2,57 +2,43 @@
|
||||
title: Overview
|
||||
---
|
||||
|
||||
Ollama integrates with a wide range of tools.
|
||||
Use Ollama from coding agents, personal assistants, and editors.
|
||||
|
||||
## Coding Agents
|
||||
Run `ollama launch` to see the latest integrations you can run from the terminal.
|
||||
|
||||
Coding assistants that can read, modify, and execute code in your projects.
|
||||
## Code in the terminal
|
||||
|
||||
- [Claude Code](/integrations/claude-code)
|
||||
- [Codex App](/integrations/codex-app)
|
||||
- [Codex CLI](/integrations/codex)
|
||||
- [Copilot CLI](/integrations/copilot-cli)
|
||||
- [Cline CLI](/integrations/cline-cli)
|
||||
- [OpenCode](/integrations/opencode)
|
||||
- [Droid](/integrations/droid)
|
||||
- [Goose](/integrations/goose)
|
||||
- [Oh My Pi](/integrations/oh-my-pi)
|
||||
- [Pi](/integrations/pi)
|
||||
- [Pool](/integrations/pool)
|
||||
|
||||
## Assistants
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Claude Code" icon="/images/launch-icons/claude-code.svg" href="/integrations/claude-code">
|
||||
Terminal coding agent with tools, vision, web search, and long context.
|
||||
</Card>
|
||||
|
||||
AI assistants that help with everyday tasks.
|
||||
<Card title="OpenCode" icon="/images/launch-icons/opencode.svg" href="/integrations/opencode">
|
||||
Open-source coding agent that edits, runs, and iterates on code.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
- [OpenClaw](/integrations/openclaw)
|
||||
- [Hermes Agent](/integrations/hermes)
|
||||
- [Hermes Desktop](/integrations/hermes-desktop)
|
||||
## Connect an assistant
|
||||
|
||||
## IDEs & Editors
|
||||
Assistants with memory, skills, and messaging app access.
|
||||
|
||||
Native integrations for popular development environments.
|
||||
<CardGroup cols={2}>
|
||||
<Card title="OpenClaw" icon="/images/launch-icons/openclaw.svg" href="/integrations/openclaw">
|
||||
Personal assistant for messaging apps and everyday tasks.
|
||||
</Card>
|
||||
|
||||
- [VS Code](/integrations/vscode)
|
||||
- [Cline](/integrations/cline)
|
||||
- [Roo Code](/integrations/roo-code)
|
||||
- [JetBrains](/integrations/jetbrains)
|
||||
- [Xcode](/integrations/xcode)
|
||||
- [Zed](/integrations/zed)
|
||||
<Card title="Hermes Agent" icon="/images/launch-icons/hermes-agent.svg" href="/integrations/hermes">
|
||||
Open-source agent with self-improving skills, memory, and messaging.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Chat & RAG
|
||||
## Work in your editor
|
||||
|
||||
Chat interfaces and retrieval-augmented generation platforms.
|
||||
Use Ollama models inside your editor.
|
||||
|
||||
- [Onyx](/integrations/onyx)
|
||||
|
||||
## Automation
|
||||
|
||||
Workflow automation platforms with AI integration.
|
||||
|
||||
- [n8n](/integrations/n8n)
|
||||
|
||||
## Notebooks
|
||||
|
||||
Interactive computing environments with AI capabilities.
|
||||
|
||||
- [marimo](/integrations/marimo)
|
||||
<CardGroup cols={2}>
|
||||
<Card title="VS Code" icon="/images/launch-icons/vscode.svg" href="/integrations/vscode">
|
||||
Use Ollama models in VS Code Chat.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
+129
-15
@@ -2,30 +2,144 @@
|
||||
title: OpenCode
|
||||
---
|
||||
|
||||
OpenCode is an open-source AI coding assistant that runs in your terminal.
|
||||
[OpenCode](https://opencode.ai) is an open-source coding agent that runs in your terminal, reads your project, edits files, and runs commands.
|
||||
|
||||
## Install
|
||||
Ollama configures OpenCode to use local and cloud models.
|
||||
|
||||
Install the [OpenCode CLI](https://opencode.ai):
|
||||
## Get started
|
||||
|
||||
```bash
|
||||
curl -fsSL https://opencode.ai/install | bash
|
||||
```
|
||||
Launch OpenCode with Ollama:
|
||||
|
||||
<Note>OpenCode requires a larger context window. It is recommended to use a context window of at least 64k tokens. See [Context length](/context-length) for more information.</Note>
|
||||
|
||||
## Usage with Ollama
|
||||
|
||||
### Quick setup
|
||||
|
||||
```bash
|
||||
```shell
|
||||
ollama launch opencode
|
||||
```
|
||||
|
||||
To configure without launching:
|
||||
## Capabilities
|
||||
|
||||
<div className="capability-list capability-list-full">
|
||||
<div className="capability-list-grid">
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="comment" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Chat</div>
|
||||
<div className="capability-list-copy">Ask questions about a repository or task</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="terminal" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Command line</div>
|
||||
<div className="capability-list-copy">Run commands from your working directory</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="code" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">File edits</div>
|
||||
<div className="capability-list-copy">Read and edit files in your project</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="users" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Subagents</div>
|
||||
<div className="capability-list-copy">Split work across tasks</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="file-text" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Web fetch</div>
|
||||
<div className="capability-list-copy">Fetch and summarize web pages</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="capability-list-item">
|
||||
<div className="capability-list-icon"><Icon icon="image" /></div>
|
||||
<div>
|
||||
<div className="capability-list-heading">Vision</div>
|
||||
<div className="capability-list-copy">Send images and screenshots</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
## Models
|
||||
|
||||
Choose a model with enough context for your repository.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Cloud models" icon="cloud" href="https://ollama.com/search?c=cloud">
|
||||
Use larger models without downloading them.
|
||||
</Card>
|
||||
|
||||
<Card title="Local models" icon="hard-drive" href="https://ollama.com/search?c=tools">
|
||||
Choose a model and set a 64k+ context window.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
<Note>OpenCode requires a context length of 64k or higher. See [Context length](/context-length) for more information.</Note>
|
||||
|
||||
## Manual setup
|
||||
|
||||
<p className="manual-step-title">1. Install OpenCode</p>
|
||||
|
||||
<CodeGroup>
|
||||
|
||||
```shell macOS / Linux
|
||||
curl -fsSL https://opencode.ai/install | bash
|
||||
```
|
||||
|
||||
```powershell Windows
|
||||
npm install -g opencode-ai
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
<p className="manual-step-title">2. Configure Ollama as a provider</p>
|
||||
|
||||
Add an Ollama provider to `opencode.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"$schema": "https://opencode.ai/config.json",
|
||||
"provider": {
|
||||
"ollama": {
|
||||
"npm": "@ai-sdk/openai-compatible",
|
||||
"name": "Ollama",
|
||||
"options": {
|
||||
"baseURL": "http://localhost:11434/v1"
|
||||
},
|
||||
"models": {
|
||||
"qwen3.5": {
|
||||
"name": "qwen3.5"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
<p className="manual-step-title">3. Run OpenCode</p>
|
||||
|
||||
```shell
|
||||
opencode
|
||||
```
|
||||
|
||||
To configure OpenCode with Ollama without starting an interactive session:
|
||||
|
||||
```shell
|
||||
ollama launch opencode --config
|
||||
```
|
||||
|
||||
<Note>`ollama launch opencode` passes its configuration to OpenCode inline via the `OPENCODE_CONFIG_CONTENT` environment variable. OpenCode deep-merges its config sources on startup, so anything you declare in `~/.config/opencode/opencode.json` is still respected and available inside OpenCode. Models declared only in `opencode.json` won't appear in `ollama launch`'s model-selection menu.</Note>
|
||||
### Configuration precedence
|
||||
|
||||
`ollama launch opencode` starts OpenCode with an inline config for the selected Ollama model. It does not overwrite `~/.config/opencode/opencode.json`; existing OpenCode settings still apply.
|
||||
|
||||
Models defined only in `opencode.json` do not appear in the `ollama launch` model picker.
|
||||
|
||||
See OpenCode's [config precedence](https://opencode.ai/docs/config/#precedence-order).
|
||||
|
||||
@@ -2,84 +2,57 @@
|
||||
title: VS Code
|
||||
---
|
||||
|
||||
VS Code includes built-in AI chat through GitHub Copilot Chat. Ollama models can be used directly in the Copilot Chat model picker.
|
||||
Use Ollama models in VS Code Chat with the [Ollama extension](https://marketplace.visualstudio.com/items?itemName=Ollama.ollama).
|
||||
|
||||
## Requirements
|
||||
|
||||
|
||||
- [Visual Studio Code 1.127 or newer](https://code.visualstudio.com/download)
|
||||
- Ollama installed and running
|
||||
- At least one local or cloud model available in Ollama
|
||||
|
||||
Earlier VS Code versions do not reliably cancel requests from language model providers.
|
||||
|
||||
## Prerequisites
|
||||
Ollama 0.17.6 or newer is recommended for cloud model sign-in and richer model metadata. Older versions may still work with local models.
|
||||
|
||||
- Ollama v0.18.3+
|
||||
- [VS Code 1.113+](https://code.visualstudio.com/download)
|
||||
- [GitHub Copilot Chat extension 0.41.0+](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot-chat)
|
||||
## Install the extension
|
||||
|
||||
<Note> VS Code requires you to be logged in to use its model selector, even for custom models. This doesn't require a paid GitHub Copilot account; GitHub Copilot Free will enable model selection for custom models.</Note>
|
||||
1. Install the [Ollama extension](https://marketplace.visualstudio.com/items?itemName=Ollama.ollama) from the VS Code Marketplace.
|
||||
2. Open Chat in VS Code.
|
||||
3. Open the model picker at the bottom of the chat input.
|
||||
4. Choose a model from the **Ollama** section.
|
||||
|
||||
## Quick setup
|
||||
The extension discovers models from `http://127.0.0.1:11434` by default.
|
||||
|
||||
## Add a model
|
||||
|
||||
Pull a local model:
|
||||
|
||||
```shell
|
||||
ollama launch vscode
|
||||
ollama pull qwen3.6
|
||||
```
|
||||
|
||||
Recommended models will be shown after running the command. See the latest models at [ollama.com](https://ollama.com/search?c=tools).
|
||||
|
||||
Make sure **Local** is selected at the bottom of the Copilot Chat panel to use your Ollama models.
|
||||
<div style={{ display: "flex", justifyContent: "center" }}>
|
||||
<img
|
||||
src="/images/local.png"
|
||||
alt="Ollama Local Models"
|
||||
width="60%"
|
||||
style={{ borderRadius: "4px", marginTop: "10px", marginBottom: "10px" }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
|
||||
## Run directly with a model
|
||||
To use a cloud model, pull it and sign in:
|
||||
|
||||
```shell
|
||||
ollama launch vscode --model qwen3.5:cloud
|
||||
ollama pull kimi-k2.6:cloud
|
||||
ollama signin
|
||||
```
|
||||
Cloud models are also available at [ollama.com](https://ollama.com/search?c=cloud).
|
||||
|
||||
## Manual setup
|
||||
Local models do not require sign-in.
|
||||
|
||||
To configure Ollama manually without `ollama launch`:
|
||||
## Context length
|
||||
|
||||
1. Open the **Copilot Chat** side bar from the top right corner
|
||||
<div style={{ display: "flex", justifyContent: "center" }}>
|
||||
<img
|
||||
src="/images/vscode-sidebar.png"
|
||||
alt="VS Code chat Sidebar"
|
||||
width="75%"
|
||||
style={{ borderRadius: "4px" }}
|
||||
/>
|
||||
</div>
|
||||
2. Click the **settings gear icon** (<Icon icon="gear" />) to bring up the Language Models window
|
||||
<div style={{ display: "flex", justifyContent: "center" }}>
|
||||
<img
|
||||
src="/images/vscode-other-models.png"
|
||||
alt="VS Code model picker"
|
||||
width="75%"
|
||||
style={{ borderRadius: "4px" }}
|
||||
/>
|
||||
</div>
|
||||
3. Click **Add Models** and select **Ollama** to load all your Ollama models into VS Code
|
||||
<div style={{ display: "flex", justifyContent: "center" }}>
|
||||
<img
|
||||
src="/images/vscode-add-ollama.png"
|
||||
alt="VS Code model options dropdown to add ollama models"
|
||||
width="75%"
|
||||
style={{ borderRadius: "4px" }}
|
||||
/>
|
||||
</div>
|
||||
VS Code may show a model's maximum supported context length even when Ollama allocates a smaller context at runtime.
|
||||
|
||||
4. Click the **Unhide** button in the model picker to show your Ollama models
|
||||
<div style={{ display: "flex", justifyContent: "center" }}>
|
||||
<img
|
||||
src="/images/vscode-unhide.png"
|
||||
alt="VS Code unhide models button"
|
||||
width="75%"
|
||||
style={{ borderRadius: "4px" }}
|
||||
/>
|
||||
</div>
|
||||
For local models, open Ollama **Settings**, set the context length to at least 64k, reload the VS Code window, and resend your prompt. See [Context length](/context-length) for more information.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
If Ollama models do not appear in the model picker:
|
||||
|
||||
1. Make sure Ollama is running.
|
||||
2. Run `ollama list` and confirm that models are available.
|
||||
3. Run **Ollama: Refresh Models** from the Command Palette.
|
||||
4. Run **Ollama: Diagnose Models** and check the **Ollama** output channel.
|
||||
|
||||
If a cloud model asks you to sign in, run `ollama signin`.
|
||||
|
||||
+1
-1
@@ -116,7 +116,7 @@ sudo systemctl status ollama
|
||||
While AMD has contributed the `amdgpu` driver upstream to the official linux
|
||||
kernel source, the version is older and may not support all ROCm features. We
|
||||
recommend you install the latest driver from
|
||||
https://www.amd.com/en/support/linux-drivers for best support of your Radeon
|
||||
https://www.amd.com/en/support/download/linux-drivers.html for best support of your Radeon
|
||||
GPU.
|
||||
</Note>
|
||||
|
||||
|
||||
+2
-6
@@ -107,12 +107,8 @@ FROM <model name>:<tag>
|
||||
FROM llama3.2
|
||||
```
|
||||
|
||||
<Card title="Base Models" href="https://github.com/ollama/ollama#model-library">
|
||||
A list of available base models
|
||||
</Card>
|
||||
|
||||
<Card title="Base Models" href="https://ollama.com/library">
|
||||
Additional models can be found at
|
||||
<Card title="Model library" href="https://ollama.com/library">
|
||||
Browse available models
|
||||
</Card>
|
||||
|
||||
#### Build from a Safetensors model
|
||||
|
||||
+10
-4
@@ -99,8 +99,8 @@ components:
|
||||
oneOf:
|
||||
- type: boolean
|
||||
- type: string
|
||||
enum: [high, medium, low]
|
||||
description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low") for supported models.
|
||||
enum: [high, medium, low, max]
|
||||
description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low", "max") for supported models, with "max" requesting the highest thinking level.
|
||||
raw:
|
||||
type: boolean
|
||||
description: When true, returns the raw response from the model without any prompt templating
|
||||
@@ -291,8 +291,8 @@ components:
|
||||
oneOf:
|
||||
- type: boolean
|
||||
- type: string
|
||||
enum: [high, medium, low]
|
||||
description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low") for supported models.
|
||||
enum: [high, medium, low, max]
|
||||
description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low", "max") for supported models, with "max" requesting the highest thinking level.
|
||||
keep_alive:
|
||||
oneOf:
|
||||
- type: string
|
||||
@@ -483,6 +483,12 @@ components:
|
||||
template:
|
||||
type: string
|
||||
description: Prompt template to use for the model
|
||||
renderer:
|
||||
type: string
|
||||
description: Name of the renderer for the model
|
||||
parser:
|
||||
type: string
|
||||
description: Name of the parser for the model
|
||||
license:
|
||||
oneOf:
|
||||
- type: string
|
||||
|
||||
+26
-33
@@ -2,7 +2,11 @@
|
||||
title: Quickstart
|
||||
---
|
||||
|
||||
Ollama is available on macOS, Windows, and Linux.
|
||||
Install Ollama and get your first response.
|
||||
|
||||
## 1. Download Ollama
|
||||
|
||||
Ollama runs on macOS, Windows, and Linux.
|
||||
|
||||
<a
|
||||
href="https://ollama.com/download"
|
||||
@@ -12,56 +16,45 @@ Ollama is available on macOS, Windows, and Linux.
|
||||
Download Ollama
|
||||
</a>
|
||||
|
||||
## Get Started
|
||||
## 2. Open the menu
|
||||
|
||||
Run `ollama` in your terminal to open the interactive menu:
|
||||
|
||||
```sh
|
||||
```shell
|
||||
ollama
|
||||
```
|
||||
|
||||
Navigate with `↑/↓`, press `enter` to launch, `→` to change model, and `esc` to quit.
|
||||
From the menu you can:
|
||||
|
||||
The menu provides quick access to:
|
||||
- **Run a model** - Start an interactive chat
|
||||
- **Launch tools** - Claude Code, Codex, OpenClaw, and more
|
||||
- **Additional integrations** - Available under "More..."
|
||||
- **Launch tools** - [Claude Code](/integrations/claude-code), [OpenClaw](/integrations/openclaw), [VS Code](/integrations/vscode), and more
|
||||
|
||||
## Assistants
|
||||
## 3. Start a chat
|
||||
|
||||
Launch [OpenClaw](/integrations/openclaw), a personal AI with 100+ skills:
|
||||
Run a model to start your first chat.
|
||||
|
||||
```sh
|
||||
ollama launch openclaw
|
||||
```shell
|
||||
ollama run gemma4
|
||||
```
|
||||
|
||||
## Coding
|
||||
Cloud models work the same way:
|
||||
|
||||
Launch [Claude Code](/integrations/claude-code) and other coding tools with Ollama models:
|
||||
|
||||
```sh
|
||||
ollama launch claude
|
||||
```shell
|
||||
ollama run gemma4:cloud
|
||||
```
|
||||
|
||||
```sh
|
||||
ollama launch codex
|
||||
Send your first message:
|
||||
|
||||
```text
|
||||
Explain why the sky is blue in one paragraph.
|
||||
```
|
||||
|
||||
```sh
|
||||
ollama launch opencode
|
||||
To leave the chat, type:
|
||||
|
||||
```shell
|
||||
/bye
|
||||
```
|
||||
|
||||
See [integrations](/integrations) for all supported tools.
|
||||
## Next steps
|
||||
|
||||
## API
|
||||
|
||||
Use the [API](/api) to integrate Ollama into your applications:
|
||||
|
||||
```sh
|
||||
curl http://localhost:11434/api/chat -d '{
|
||||
"model": "gemma4",
|
||||
"messages": [{ "role": "user", "content": "Hello!" }]
|
||||
}'
|
||||
```
|
||||
|
||||
See the [API documentation](/api) for Python, JavaScript, and other integrations.
|
||||
Use a model with an [integration](/integrations), make an [API request](/api/introduction), or browse more [models](https://ollama.com/search).
|
||||
|
||||
@@ -14,3 +14,117 @@ pre, code, .font-mono {
|
||||
color: #666;
|
||||
font-weight: 400;
|
||||
}
|
||||
|
||||
.capability-list {
|
||||
border-top: 1px solid #e5e5e5;
|
||||
border-bottom: 1px solid #e5e5e5;
|
||||
display: grid;
|
||||
gap: 2rem;
|
||||
grid-template-columns: 7rem minmax(0, 1fr);
|
||||
margin: 1.5rem 0 2rem;
|
||||
padding: 2rem 0;
|
||||
}
|
||||
|
||||
.capability-list-title {
|
||||
color: #171717;
|
||||
font-size: 1rem;
|
||||
line-height: 1.5rem;
|
||||
}
|
||||
|
||||
.capability-list-full {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
|
||||
.capability-list-grid {
|
||||
display: grid;
|
||||
gap: 1.75rem 2rem;
|
||||
grid-template-columns: repeat(2, minmax(0, 1fr));
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.capability-list-item {
|
||||
align-items: flex-start;
|
||||
display: grid;
|
||||
gap: 0.75rem;
|
||||
grid-template-columns: 2rem minmax(0, 1fr);
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.capability-list-icon {
|
||||
align-items: center;
|
||||
background: #f1f1f1;
|
||||
border-radius: 0.75rem;
|
||||
color: #171717;
|
||||
display: flex;
|
||||
height: 2rem;
|
||||
justify-content: center;
|
||||
width: 2rem;
|
||||
}
|
||||
|
||||
.capability-list-icon svg {
|
||||
height: 1rem;
|
||||
width: 1rem;
|
||||
}
|
||||
|
||||
.capability-list-heading {
|
||||
color: #171717;
|
||||
font-size: 1rem;
|
||||
font-weight: 600;
|
||||
line-height: 1.375rem;
|
||||
}
|
||||
|
||||
.capability-list-copy {
|
||||
color: #737373;
|
||||
font-size: 0.95rem;
|
||||
line-height: 1.375rem;
|
||||
}
|
||||
|
||||
.manual-step-title {
|
||||
color: #171717;
|
||||
font-size: 0.95rem;
|
||||
font-weight: 600;
|
||||
line-height: 1.375rem;
|
||||
margin: 1.25rem 0 0.75rem;
|
||||
}
|
||||
|
||||
.dark .capability-list {
|
||||
border-color: #262626;
|
||||
}
|
||||
|
||||
.dark .capability-list-title,
|
||||
.dark .capability-list-heading,
|
||||
.dark .manual-step-title {
|
||||
color: #fafafa;
|
||||
}
|
||||
|
||||
.dark .capability-list-icon {
|
||||
background: #262626;
|
||||
color: #fafafa;
|
||||
}
|
||||
|
||||
.dark .capability-list-copy {
|
||||
color: #a3a3a3;
|
||||
}
|
||||
|
||||
@media (max-width: 920px) {
|
||||
.capability-list {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
|
||||
.capability-list-grid {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
}
|
||||
|
||||
.accordion-group {
|
||||
border-style: none;
|
||||
border-radius: 0;
|
||||
}
|
||||
|
||||
.accordion-group div[id*="-accordion-children"] {
|
||||
margin-inline: calc(var(--spacing) * 1);
|
||||
}
|
||||
|
||||
.accordion-group details summary {
|
||||
padding-inline: 0;
|
||||
}
|
||||
|
||||
@@ -137,7 +137,7 @@ After upgrading, reboot and restart Ollama.
|
||||
|
||||
If you experience gibberish responses when models load across multiple AMD GPUs on Linux, see the following guide.
|
||||
|
||||
- https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/mgpu.html#mgpu-known-issues-and-limitations
|
||||
- https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/install/installrad/native_linux/mgpu.html#mgpu-known-issues-and-limitations
|
||||
|
||||
## Windows Terminal Errors
|
||||
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ terminal application. As usual the Ollama [API](/api) will be served on
|
||||
## System Requirements
|
||||
|
||||
- Windows 10 22H2 or newer, Home or Pro
|
||||
- NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
|
||||
- NVIDIA 551.61 or newer Drivers if you have an NVIDIA card
|
||||
- AMD ROCm v7 / HIP7-capable driver stack for ROCm acceleration, or a Vulkan-capable AMD Radeon driver for Vulkan acceleration
|
||||
|
||||
Ollama uses unicode characters for progress indication, which may render as unknown squares in some older terminal fonts in Windows 10. If you see this, try changing your terminal font settings.
|
||||
|
||||
Reference in New Issue
Block a user