ai-toolkit vs OneTrainer vs Musubi Tuner

The three trainers most used for current image models, compared by model support (from each project's README) and activity (GitHub API).

Model	ai-toolkit	OneTrainer	musubi-tuner
Krea 2 / Krea 2 Turbo	supported (Raw + Turbo, incl. edit training)	supported (per community blog; not in README list)	supported (fp8 / ConvRot int8 base)
FLUX.2 dev (32B)	supported (reference)	supported	supported
FLUX.2 klein (4B)	supported (klein base 4B and 9B)	supported	supported
Z-Image	supported (Z-Image, Turbo, De-Turbo)	supported	supported
SDXL	supported	supported	not listed
FLUX.1	supported	supported	FLUX.1 Kontext only

Activity

Trainer	Stars	Last commit	Latest release
ai-toolkit	12321	2026-10-16	none published
OneTrainer	3243	2026-10-16	none published
musubi-tuner	2098	2026-10-12	v0.3.6

ai-toolkit: widest new-model support (Krea 2 Raw/Turbo incl. edit, FLUX.2 dev/klein, Z-Image); community calls it the easiest for Flux/Krea (r/StableDiffusion).
OneTrainer: GUI + CLI, broad model list incl. FLUX.2 and Z-Image; users report good VRAM use and speed, harder to configure.
musubi-tuner: CLI scripts from kohya; Krea 2 with fp8 or ConvRot int8 base weights (faster on RTX 30 and older), FLUX.2, Z-Image; 12 GB+ recommended for image training.

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Data updated 2026-10-16. Some provider links may be referral links. unknown = not yet verified.