DATASHEET // KOHYA-SS
Kohya_ss
The standard SDXL/Flux LoRA training UI.
OPEN SOURCE12–24 GB VRAMRuns locally
Actually FreeNo SignupOpen SourceWatermark-FreeHobbyist-OK
Visit Kohya_ssUPDATED 2026-05-07 · DIRECT LINK
HARDWARE REQUIREMENTS //
Runs locally · High-end GPU (16–24 GB)
Min VRAM
12 GB
Rec. VRAM
24 GB
Min RAM
32 GB
Rec. RAM
64 GB
Disk
100 GB
GPU class
High-end GPU
CUDA 12.xNo Apple SiliconGPU RequiredQuant: FP16, BF16, FP8
SDXL LoRA fits 12 GB. Flux LoRA realistically wants 24 GB with FP8 or block-swapping.
[ EDITORIAL PICK ]
Why we recommend Kohya_ss
- Open source
Source is public — you can audit it, fork it, and you'll never lose access to your workflows if Kohya_ss the company changes direction.
- Runs on 12 GB
Comfortable on a mid-range consumer card — no need to remortgage for an A100.
- Top-tier pick
Power-user score 91/100 — consistently rated highly by people who use this every day, not just benchmark chasers.
- 3 quant formats
Supports FP16, BF16, FP8 — you can dial VRAM use up or down to match your card.
[ EVIDENCE NOTE ]
Documentation-led datasheet
This page summarizes upstream documentation, release information, and editorially reviewed catalogue fields. It is not presented as a hands-on benchmark. Verify changing requirements at the official project; report stale data through our corrections channel.
AT-A-GLANCE SIGNALS //
DERIVED FROM THIS PAGE'S DATA- Install difficultyStandard
A standard local install — download, install dependencies, point at your GPU.
- Hardware comfortMainstream
Needs 12 GB minimum — RTX 3060 12GB or 4070 territory.
- EcosystemActive community
Open source plus 4 community resources we've vetted — there are people to ask.
- VerificationRecent
Catalogue entry last updated 70 days ago — re-verification due soon.
[ COMMUNITY GUIDES & WORKFLOWS ]
Tutorials & deep-dives for Kohya_ss
Hand-picked from YouTube, Reddit, GitHub, and the wider web. Each link goes straight to the source — we don't intercept or rewrite anything.
[ MORE IN THIS NICHE ]
Other training & fine-tuning tools we rate
Three picks across different tradeoffs — so you don't end up with three near-clones of Kohya_ss.
LIGHTEST HARDWARE //
Transformers
The library every LLM ships against first.
OPEN SOURCE2–24 GB VRAM
BEST FREE OPTION //
Diffusers
Hugging Face's go-to library for every diffusion model.
OPEN SOURCE4–12 GB VRAM
TOP QUALITY //
sd-scripts (Kohya)
The underlying scripts powering Kohya & most LoRA trainers.
OPEN SOURCE8–12 GB VRAM
What is Kohya_ss?
The most-used GUI for training LoRAs, LyCORIS, and full fine-tunes on SD1.5, SDXL, SD3, and Flux. Sensible defaults plus every advanced knob you might need.
Pros & cons
✓ PROS
- De-facto LoRA trainer
- Active community presets
- Supports Flux LoRA training
– CONS
- Gradio UI is dense
- Flux training needs 24 GB+ realistically
What's actually free?
Free / OSS.
✓ Actually FreeNo SignupOpen SourceWatermark-Free
