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OneTrainer

Nerogar
open source / Overall score: 2.5

OneTrainer is a training application for diffusion models, supporting full fine-tuning, LoRA and embeddings across Stable Diffusion 1.5 through 3.5, SDXL, FLUX.1, FLUX.2, Qwen Image, PixArt, Sana and Hunyuan Video. It includes masked training, EMA, aspect-ratio bucketing and multi-resolution training, and runs from either a GUI or a CLI.

Openness

5 high confidence
5.0
license
AGPL-3.0(OSI)
source
public(Nerogar/OneTrainer)
core features withheld
no — no enterprise or ee path in the repository root and no paid tier described in the README

OneTrainer is licensed under AGPL-3.0, an OSI-approved license, and the full source ships in this repository. The repository has no enterprise or paid-tier path, so nothing is withheld from what is published.

Adoption

2 low confidence
2.0

No package registry carries OneTrainer, so GitHub stars are the only adoption signal available. A star reflects attention rather than actual use, which is why this reading carries low confidence.

Capability

3 medium confidence
3.0

OneTrainer and ai-toolkit trade off as the category's diffusion-trainer pair: OneTrainer reaches further on method, with full fine-tuning and embeddings rather than only adapters, while ai-toolkit covers more modalities, including video and audio. Neither has a distributed-training story, which keeps both below the tools with wider training-scale claims.

  • https://raw.githubusercontent.com/Nerogar/OneTrainer/master/README.md recorded 2026-10-07

    Features section lists supported models from Ernie Image and Z-Image through SD 1.5-3.5, SDXL, FLUX.1, Flux.2 Dev and Klein, PixArt, Sana and Hunyuan Video; training methods full fine-tuning, LoRA and embeddings; and masked training, automatic backups, image augmentation, TensorBoard, EMA with CPU offload, aspect-ratio bucketing and multi-resolution training.

Verified 2026-09-27