---
id: workflow.weights-training.choose-method
title: Choose between SFT and DPO
summary: Choose the learner target that fits the distinction you want the model to learn.
kind: task
product_area: weights_training
status: stable
updated: 2026-11-11
canonical: /docs/weights-training/choose-method
---

# Choose between SFT and DPO

Choose the learner target that fits the distinction you want the model to learn.

## Prerequisites

A training objective grounded in selected benchmark criteria and access to Weights training.

## Steps

1. For supervised fine-tuning, identify the target behavior an appropriate demonstration should teach.
2. For preference optimization, identify a meaningful preference between responses to the same input and the rubric that explains it.
3. Create the preparation with the intended Benchmark Version and supported method. Inspect the resulting target fields in Dataset.
4. Check that the export profile, connected service, and model family support the method and material types before a training handoff.

## Object and state changes

The preparation records the method and selected scope. Dataset and provider compatibility are separate checks.

## Success criteria

Each example has a usable demonstration target or a meaningful preferred/rejected distinction for the chosen method.

## Common failure modes

Choosing a method because a provider accepts the file; constructing preference pairs whose difference does not reflect the intended standard.

## Related reference pages

{% related-card-grid title="Continue this workflow" %}
- [Prepare data for weights training](/docs/weights-training)
{% /related-card-grid %}

## Related troubleshooting pages

{% related-card-grid title="Resolve a problem" %}
- [Synthetic Cases That Feel Unrealistic](/docs/troubleshooting/unrealistic-synthetic-cases)
- [Unbalanced Coverage](/docs/troubleshooting/unbalanced-coverage)
{% /related-card-grid %}