> ## 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 Roo Code with SaladCloud
> Learn how to use the Roo Code AI coding agent in VS Code with a self-hosted model on SaladCloud.
*Last Updated: May 18, 2026*
## Introduction
[Roo Code](https://roocode.com) is an open-source AI coding agent for VS Code that gives you a whole dev team of AI
agents in your editor. It supports multiple specialized modes (Code, Architect, Ask, Debug, Test), MCP server
integrations, and boomerang tasks - breaking complex work into subtasks handled by specialized subagents.
Model-agnostic, highly configurable, secure and transparent.
Roo Code works with SaladCloud in two ways:
* **[Salad AI Gateway](/ai-gateway/explanation/overview)** - no infrastructure to deploy or manage. Sign up for access,
point Roo Code 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.
## Prerequisites
Before getting started, make sure you have:
* A [SaladCloud account](https://portal.salad.com)
* VS Code installed on your machine
## 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 best fit for agentic coding is the Qwen3.6-35B-A3B (llama.cpp) recipe. 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`)
* **API key** (from your SaladCloud organization settings, if you enabled authentication)
### Step 2: Install Roo Code in VS Code
1. Open VS Code and go to the Extensions view (`Ctrl+Shift+X` or `Cmd+Shift+X` on macOS)
2. Search for **Roo Code**
3. Click **Install** on the Roo Code extension by roocode.com
4. Once installed, click the Roo Code icon in the sidebar to open the panel
### Step 3: Configure Roo Code to Use Your SaladCloud Endpoint
1. In the Roo Code panel, click the **settings icon** or on the first run, you'll be prompted to configure your API
provider
2. Choose 3rd-party Provider and set **API Provider** to `OpenAI Compatible`
3. Fill in the fields based on your chosen backend:
* **Base URL**: `https://ai.salad.cloud/v1`
* **API Key**: your Salad API key
* **Model ID**: e.g. `qwen3.6-35b-a3b`
No custom headers are needed - your Salad API key in the API Key field is all that's required.
* **Base URL**: your SaladCloud endpoint URL (e.g., `https://your-endpoint.salad.cloud/v1`)
* **API Key**: any non-empty string (e.g., `dummy`) - authentication is handled via a custom header below
* **Model ID**: the model name from your deployment (e.g., `qwen3.6-35b-a3b`)
If your deployment has authentication enabled, expand **Custom Headers** and add:
* Header name: `Salad-Api-Key`
* Header value: your SaladCloud API key
### Step 4: Test the Connection
Start with a simple task to verify everything is working:
> "Create a hello world Python script that prints 'Hello from SaladCloud!'"
If Roo Code successfully creates the file, your setup is complete.
## Tips for Best Results
### Use Incremental Prompting for Complex Tasks
SaladCloud has a 100-second request timeout. For large multi-file tasks, instruct Roo Code to work incrementally:
> "Important: work incrementally. Create and save each file one at a time before moving on to the next."
### Choose the Right Mode
* **Code** - general code generation and editing
* **Architect** - high-level design and planning
* **Ask** - questions and explanations without file modifications
* **Debug** - focused on diagnosing and fixing bugs
* **Test** - generating and running tests
### Model Recommendations
* **Qwen 3.6-35B-A3B**: Best balance of capability and cost for agentic coding tasks
* **Qwen 3.5-9B**: Suitable for simpler tasks; may struggle with complex multi-file edits