> ## 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.

# Qwen3.6-27B-unsloth with llama.cpp recipe

> Serve Qwen3.6-27B-unsloth with llama.cpp as an OpenAI-compatible API for OpenClaw, OpenCode, and other tools.

*Last Updated: April 23, 2026*

<Tip>Deploy from the [SaladCloud Portal](https://portal.salad.com).</Tip>

## Overview

This recipe runs `Qwen3.6-27B-unsloth` with the official [llama.cpp](https://github.com/ggml-org/llama.cpp) CUDA server
on a Salad GPU. The model downloads automatically on startup, the built-in llama.cpp web UI is available at your
deployment URL, and the container exposes an OpenAI-compatible API for tools such as OpenClaw, OpenCode, and other
compatible clients.

This recipe is designed to be easy for nontechnical users:

* the model is already chosen for you
* it is public by default, so you can test it immediately after deployment
* thinking is enabled by default
* you can start with the built-in web UI, then connect other tools later

Qwen describes Qwen3.6-27B-unsloth as a coding-focused dense model with stronger agentic coding behavior and support for
preserving reasoning context across turns.

## Quick Start

1. Open the [SaladCloud Portal](https://portal.salad.com).
2. Deploy the **Qwen3.6-27B-unsloth (llama.cpp)** recipe.
3. Enter a **Container Group Name**.
4. Decide whether to enable **Require Container Gateway Authentication**:
   * Disabled: public access.
   * Enabled: requests must include your SaladCloud API key.
5. Choose whether to keep **Enable Thinking / Reasoning** turned on.
6. Deploy and wait for the first startup to finish.

<Callout variation="note">
  Model is downloaded at startup, so the first startup can take several minutes before the deployment becomes ready.
</Callout>

Once the container is ready, you can either open the built-in UI in a browser or connect an OpenAI-compatible client to
`/v1/chat/completions`.

## Use With OpenClaw

If you want to connect this recipe to OpenClaw or other agentic tools, follow these guides:

* [Use OpenClaw with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-openclaw-with-saladcloud)
* [Use OpenCode with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-opencode-with-saladcloud)
* [Use Cline with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-cline-with-saladcloud)
* [Use Aider with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-aider-with-saladcloud)
* [Use Kilo Code with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-kilo-code-with-saladcloud)
* [Use Roo Code with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-roo-code-with-saladcloud)
* [Use Continue with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-continue-with-saladcloud)
* [Use Vercel AI SDK with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-vercel-ai-sdk-with-saladcloud)
* [Use Goose with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-goose-with-saladcloud)
* [Use Hermes with a Salad-hosted LLM](/container-engine/tutorials/agentic-tools/use-hermes-agent-with-saladcloud)

## Defaults

The recipe comes preconfigured with these defaults:

* Model source: `unsloth/Qwen3.6-27B-GGUF`
* Model file: `Qwen3.6-27B-UD-Q4_K_XL.gguf`
* Model alias: `qwen3.6-27b`
* Configured context size: `131072`
* Native model context: `262144`
* Parallel slots: `1`
* Thinking: enabled by default
* Sampling defaults: `temperature 0.6`, `top_p 0.95`, `min_p 0.0`, `top_k 20`
* Authentication: disabled by default

`temperature`, `top_p`, and `min_p` are startup defaults. You can still override them per request in your inference
payload.

The recipe defaults to `131072` tokens because that is a more practical single-GPU llama.cpp starting point. If you need
more context later, you can raise `LLAMA_ARG_CTX_SIZE` in Advanced Configuration.

## Thinking Mode

Thinking is enabled by default.

Qwen3.6 does not officially rely on prompt switches such as `/think` or `/no_think` in this recipe. Instead:

* turn off **Enable Thinking / Reasoning** in the deployment form to make non-thinking mode the default
* or pass `chat_template_kwargs: {"enable_thinking": false}` in clients that support extra request fields

Advanced clients can also request preserved reasoning context across turns with
`chat_template_kwargs: {"preserve_thinking": true}`.

## Authentication

**Require Container Gateway Authentication** is available in the deployment form and is unchecked by default.

* Disabled: anyone with the URL can call the API.
* Enabled: every request must include the `Salad-Api-Key` header.

If you enable authentication, see [Sending Requests](/container-engine/how-to-guides/gateway/sending-requests) for the
header format.

## Example Request

```bash theme={null}
curl https://<your-dns>.salad.cloud/v1/chat/completions \
  -X POST \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "qwen3.6-27b",
    "messages": [
      {"role": "system", "content": "You are a helpful coding assistant."},
      {"role": "user", "content": "Write a short explanation of why preserving reasoning context can help with iterative coding tasks."}
    ],
    "max_tokens": 256
  }'
```

If you enabled authentication during deployment, add:

```bash theme={null}
-H 'Salad-Api-Key: <api-key>'
```

## For Technical Users

If you want to tune llama.cpp later, open the container group in the SaladCloud Portal and edit **Advanced
Configuration**.

Useful environment variables include:

* `LLAMA_ARG_HF_REPO` to change the Hugging Face GGUF repo
* `LLAMA_ARG_HF_FILE` to choose a specific GGUF file inside the repo
* `LLAMA_ARG_MODEL_URL` to point directly to a `.gguf` file
* `LLAMA_ARG_CTX_SIZE` to change the context window
* `LLAMA_ARG_N_GPU_LAYERS` to control GPU offload
* `LLAMA_ARG_N_PARALLEL` to change concurrency

For full llama.cpp server options, see:

* [llama.cpp server docs](https://github.com/ggml-org/llama.cpp/tree/master/tools/server)
* [Server args and environment variable mapping](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md#usage)

## Source Code

* [<Icon icon="github" size="24" /> Recipe Source](https://github.com/SaladTechnologies/salad-recipes/tree/master/recipes/qwen3.6-27b-llama-cpp)
* [Unsloth Qwen3.6-27B GGUF model card](https://huggingface.co/unsloth/Qwen3.6-27B-GGUF)
* [Official Qwen3.6-27B model card](https://huggingface.co/Qwen/Qwen3.6-27B)
* [llama.cpp Project](https://github.com/ggml-org/llama.cpp)