SDXL extension & fine-tune model guide
The SDXL ecosystem is large: a base model, an optional refiner, dozens of community fine-tunes, and a stack of adapters like ControlNet, IP-Adapter, and LoRAs. Picking the right combination is the difference between fighting the model and getting clean results on the first batch. This guide maps your desired output style and use case to a concrete, compatible stack.
How it works
The tool holds a small knowledge base of the most widely used SDXL checkpoints and adapters and how they perform across styles. You select an output style and a use case, and it returns a recommended checkpoint, a note on whether the refiner is worth running, and the adapters that matter for that workflow. Because all SDXL fine-tunes share the base architecture, adapters are interchangeable as long as you match the SDXL version — so the guide focuses on which checkpoint sets the look and which adapters give you control.
Notes on the SDXL stack
- Base + refiner is the original two-model pipeline. It still works, but most fine-tunes are tuned to finish in one pass, making the refiner optional.
- RealVisXL leans photoreal, Juggernaut XL is a strong all-rounder, and DreamShaper XL balances realism with illustrative flexibility.
- Adapters add control, not style. ControlNet locks pose and structure, IP-Adapter transfers a reference look, and LoRAs inject specific subjects.
- Match the SDXL version when downloading adapters and LoRAs — 1.0-trained files work across 1.0 fine-tunes, but mismatched versions degrade output.