> ## Documentation Index
> Fetch the complete documentation index at: https://docs.inference.net/llms.txt
> Use this file to discover all available pages before exploring further.

# Choose a Recipe

> Pre-configured training setups that abstract away base model selection and training parameters.

A recipe is a pre-configured training setup. It includes a vetted base model, optimized training parameters, and compute configuration. You don't need ML expertise to pick one.

## What a recipe includes

* **Base model** — selected by the Inference team for quality on the task type
* **Optimized training parameters** — learning rate, epochs, and other hyperparameters
* **Compute configuration** — minimum 8 GPUs per training run

## How to choose

Pick based on **task difficulty and capability needs**, not specific model names. Start small and scale up only if your eval results show the smaller recipe isn't cutting it.

| Tier       | Best for                                                                                         |
| ---------- | ------------------------------------------------------------------------------------------------ |
| **Tiny**   | High-throughput tasks where speed matters most — simple classification, extraction, tagging      |
| **Small**  | Fast inference with more capability — structured output, entity extraction, routing              |
| **Medium** | Good balance of speed and intelligence — summarization, Q\&A, agentic tasks that need to be fast |
| **Large**  | Complex reasoning, multi-step tasks, difficult agentic use cases                                 |

Some recipes offer specific capabilities (like multimodal support) that are only available with certain base models. Choose those when your task requires them.

## Available recipes

These are the pre-built recipes currently available on the platform. Each one has been configured and tested by the Inference team.

| Recipe     | Base Model    | Parameters | Description                                                             |
| ---------- | ------------- | ---------- | ----------------------------------------------------------------------- |
| **Tiny**   | Qwen 3.5 0.8B | 0.8B       | Tiny and incredibly fast. Best for high-volume, low-complexity tasks.   |
| **Small**  | Qwen 3.5 4B   | 4B         | Small and incredibly fast. A good default when latency is the priority. |
| **Medium** | Qwen 3.5 9B   | 9B         | Good balance of speed and intelligence. Good as a fast agentic model.   |
| **Large**  | Qwen 3.5 27B  | 27B        | Large and intelligent. Great for difficult agentic use cases.           |

All recipes use 8x H100 GPUs and include optimized training parameters. You don't need to configure any of this — just pick the tier that fits your task.