> ## Documentation Index
> Fetch the complete documentation index at: https://docs.salad.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Use OpenClaw with SaladCloud
> Learn how to set up OpenClaw as a personal AI assistant connected to a self-hosted model on SaladCloud.
*Last Updated: May 18, 2026*
## Introduction
[OpenClaw](https://openclaw.ai) is an open-source personal AI assistant with a massive ecosystem of integrations. It
connects to messaging platforms including WhatsApp, Telegram, Slack, Discord, Signal, and iMessage, and supports custom
model providers via OpenAI-compatible endpoints. Using OpenClaw with SaladCloud gives you a fully self-hosted AI
assistant stack - your model runs on distributed GPUs, your conversations stay locally and your messaging apps if used.
OpenClaw works with SaladCloud in two ways:
* **[Salad AI Gateway](/ai-gateway/explanation/overview)** - no infrastructure to deploy or manage. Sign up for access,
point OpenClaw at a single shared endpoint, and use your Salad API key directly. Currently in closed beta with monthly
flat-rate access.
* **Self-hosted model** - deploy your own SaladCloud container group for full control over the model, hardware, and
configuration. Still very easy to set up and use.
For a step-by-step guide using OpenClaw with an Ollama deployment specifically, see the [OpenClaw + Ollama (Salad
Hosted) + Telegram](/container-engine/how-to-guides/openclaw/openclaw-ollama-salad-hosted-telegram) how-to guide.
## Prerequisites
Before getting started, make sure you have:
* A [SaladCloud account](https://portal.salad.com)
* A messaging account for OpenClaw (a Telegram bot is the simplest starting point)
## Step-by-Step Setup
### Step 1: Choose Your Backend
Salad AI Gateway is the fastest way to get started - no container groups to deploy, no cold starts to wait for.
1. Sign up for early access at [salad.com/ai-gateway](https://salad.com/ai-gateway).
2. Once approved, find your **Salad API key** in the [portal](https://portal.salad.com/api-key).
Available models:
| Model | Description |
| :---------------- | :----------------------------------------------------------------------- |
| `qwen3.6-35b-a3b` | Qwen 3.6 35B-A3B - best for agentic tasks, coding, and complex reasoning |
| `qwen3.6-27b` | Qwen 3.6 27B - strong balance of capability and speed |
| `qwen3.5-9b` | Qwen 3.5 9B - fastest response times, suited for lighter tasks |
First, deploy an OpenAI-compatible LLM server on SaladCloud.
* Go to the [SaladCloud portal](https://portal.salad.com) and create an account if you do not already have one.
* Create an organization or choose an existing one, then click "Deploy a container group".
* Select an LLM recipe. The llama.cpp [Qwen3.6-35B-A3B](/container-engine/reference/recipes/qwen3.6-35b-a3b-llama-cpp)
recipe is well-suited for conversational assistant use cases. On the recipe page, provide a name and deploy - the
rest is preconfigured with recommended settings.
* Once deployed, your endpoint will be live and serving an OpenAI-compatible API.
Available recipes:
Ready-to-deploy recipes (best for less technical users):
* [qwen3.6-35B-A3B](/container-engine/reference/recipes/qwen3.6-35b-a3b-llama-cpp) - A powerful Mixture of Experts
model optimized for instruction-following tasks, ideal for agentic use cases.
* [qwen3.5-9b-llama-cpp](/container-engine/reference/recipes/qwen3.5-9b-llama-cpp) - Optimized for Qwen3.5 9B model
Recipes for custom deployments (best for advanced users):
* [llama.cpp](/container-engine/reference/recipes/llama-cpp) - Supports GGUF models
* [sglang](/container-engine/reference/recipes/sglang) - High-performance inference
* [vllm](/container-engine/reference/recipes/vllm) - Popular LLM serving framework
* [ollama](/container-engine/reference/recipes/ollama) - Simple model management
* [tgi](/container-engine/reference/recipes/tgi) - Hugging Face Text Generation Inference server
After deployment, note your **API endpoint URL** (e.g., `https://your-endpoint.salad.cloud`).
### Step 2: Install OpenClaw
```bash theme={null}
curl -fsSL https://openclaw.ai/install.sh | bash
```
Optional [Docker path](https://docs.openclaw.ai/install/docker) (if you prefer containerized local OpenClaw for
additional security/isolation):
```bash theme={null}
git clone https://github.com/openclaw/openclaw
cd openclaw
./docker-setup.sh
```
For full installation details, see the [OpenClaw docs](https://docs.openclaw.ai/install).
### Step 3: Run the Onboarding Wizard
Start the onboarding flow:
```bash theme={null}
openclaw onboard --install-daemon
```
During onboarding:
1. Accept the local-agent security warning (choose `Yes` only if you understand the agent can execute actions with your
local user permissions).
2. Select the quick start path.
3. **Skip model setup** - you will configure the SaladCloud provider manually in the next step.
4. Select **Telegram** when OpenClaw asks you to choose channels (see Step 4 below).
5. Complete or skip the remaining optional steps.
### Step 4: Connect Telegram
Telegram is the easiest channel to connect because it uses a bot token with no phone number required:
1. Open Telegram and search for `@BotFather`
2. Start a chat and send `/newbot`
3. Set a display name and a username ending in `_bot` (e.g., `salad_assistant_bot`)
4. Copy the bot token from BotFather's confirmation message
5. Paste the token when OpenClaw prompts for it during onboarding
6. After onboarding, open your Telegram bot - it will send a pairing code. Run the command it provides:
```bash theme={null}
openclaw pairing approve telegram
```
If you skipped Telegram during onboarding, add it manually to `~/.openclaw/openclaw.json`:
```json theme={null}
{
"channels": {
"telegram": {
"enabled": true,
"botToken": "",
"dmPolicy": "pairing",
"groups": { "*": { "requireMention": true } }
}
}
}
```
### Step 5: Configure the SaladCloud Model Provider
OpenClaw does not support adding arbitrary custom providers through the onboarding wizard. Instead, configure your
SaladCloud endpoint by editing `~/.openclaw/openclaw.json` directly.
Add the following config, merging with any existing content:
```json theme={null}
{
"models": {
"providers": {
"saladcloud": {
"baseUrl": "https://ai.salad.cloud/v1",
"apiKey": "your-salad-api-key",
"api": "openai-completions",
"models": [
{
"id": "qwen3.6-35b-a3b",
"name": "qwen3.6-35b-a3b",
"reasoning": false,
"input": ["text"],
"cost": { "input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0 },
"contextWindow": 262144,
"maxTokens": 32768
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "saladcloud/qwen3.6-35b-a3b"
}
}
}
}
```
No custom headers are needed - your Salad API key in `apiKey` is all that's required.
You can use any name for the provider key - in this example we use `saladcloud`.
Add the following config, merging with any existing content:
```json theme={null}
{
"models": {
"providers": {
"saladcloud": {
"baseUrl": "https://your-endpoint.salad.cloud/v1",
"apiKey": "dummy",
"api": "openai-completions",
"headers": {
"Salad-Api-Key": ""
},
"models": [
{
"id": "qwen3.6-35b-a3b",
"name": "qwen3.6-35b-a3b",
"reasoning": false,
"input": ["text"],
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0
},
"contextWindow": 262144,
"maxTokens": 32768
}
]
}
}
},
"agents": {
"defaults": {
"model": {
"primary": "saladcloud/qwen3.6-35b-a3b"
}
}
}
}
```
Replace `https://your-endpoint.salad.cloud/v1` with your actual endpoint URL.
Use `apiKey: 'dummy'` - not `'ollama-local'`. The string `'ollama-local'` is only recognized by OpenClaw for
providers with an `ollama`-prefixed name. For any other provider name, use `'dummy'` or any non-empty string.
If your SaladCloud deployment does not require authentication, remove the `headers` section, but if it does - make
sure to set the `Salad-Api-Key` header with your actual API key.
### Step 6: Restart and Test
Apply the config changes:
```bash theme={null}
openclaw doctor --fix
openclaw gateway restart
```
Then open your Telegram bot, or local tui and send a message:
> "Hello! Summarize what SaladCloud is in two sentences."
If the bot responds, your setup is complete. You can also access the local OpenClaw UI at `http://127.0.0.1:18789/`.
## Troubleshooting
### OpenClaw cannot reach the SaladCloud endpoint
* Confirm the container group is **Running** in the SaladCloud portal.
* Verify the `baseUrl` in your config ends with `/v1`.
* If auth is enabled, confirm the `Salad-Api-Key` header is set correctly.
* Test the endpoint directly with curl:
```bash theme={null}
curl https://your-endpoint.salad.cloud/v1/chat/completions \
-H 'Content-Type: application/json' \
-H 'Salad-Api-Key: ' \
-d '{"model": "qwen3.6-35b-a3b", "messages": [{"role": "user", "content": "Hello"}]}'
```
### Telegram bot is not responding
* Verify the `botToken` is correct in your config.
* Re-run pairing approval if needed: `openclaw pairing approve telegram `
* Check logs:
```bash theme={null}
openclaw logs --follow
```
## Tips for Best Results
### Use the 35B Model for Complex Tasks
For tasks that require complex instruction following and multi-step reasoning the Qwen 3.6-35B-A3B model provides
significantly better results than the 9B model.
### Provider Rotation
OpenClaw supports configuring multiple model providers. If you have multiple endpoints configured, you can specify which
provider to use on a per-agent basis in the config file. This allows you to route different tasks to different models or
endpoints as needed.
### Model Recommendations
* **Qwen 3.6-35B-A3B**: Best for complex assistant tasks
* **Qwen 3.5-9B**: Suitable for simple Q\&A and quick responses