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Train a Krea 2 LoRA on 12 GB VRAM

Can you train a Krea 2 LoRA on a 12 GB GPU? Here is the short version.

Exact VRAM data we have

ai-toolkit: ~20 GB at batch 1 with qfloat8; also trains on 12 GB with Krea Raw, low VRAM on, 50% transformer offload, 100% text-encoder offload, convrot 8, compile off, LoKr factor 8, 512 resolution only, and cached latents plus text embeddings. musubi: 12GB+ recommended for image training (general guidance); fp8 or --convrot_int8 halves weight VRAM

Memory-relevant settings

• Train at 1024px or higher
• Batch size >= 2 if VRAM allows
• Training at 512px can work for output up to ~2MP; add higher-res buckets gradually
• OneTrainer preview-2 branch (not master yet): LoRA on 8-bit quantized Krea 2 trains ~1.2x faster (16 GB preset); FLUX.2 16 GB preset ~1.3x; faster 8-bit math on RTX 50-series; DoRA not sped up
• Very slow steps (hundreds of seconds per step) mean the GPU is out of VRAM and swapping; lower the batch size or turn on low VRAM / offloading
• 12 GB ai-toolkit recipe (Krea Raw): low VRAM on, 50% transformer offload, 100% text-encoder offload, convrot 8 quantization, compile off, LoKr factor 8, 512 resolution only, cache latents and text embeddings. First steps can take many minutes; if the run hangs after the first step, try dropping the training adapter, a lower quant (Q6/Q4), or skipping text-encoder offload once embeddings are cached

My own Krea 2 recipe uses qfloat8 model + text encoder, low_vram, gradient checkpointing and cached latents; see the full recipe. I train it on a rented RTX 5090 (32 GB) and haven't tried it at 12 GB.

Trainers that support Krea 2

• ai-toolkit: supported (Raw + Turbo, incl. edit training)
• OneTrainer: supported (Krea 2 16 GB preset benchmarked in OneTrainer PR #1680; not in README list)
• musubi-tuner: supported (fp8 / ConvRot int8 base)
• SimpleTuner: supported

Other tiers: Krea 2 overview

Where to rent a 12 GB+ GPU

Cheapest 12 GB+ cards (2026-10-20 08:06 UTC) from RunPod and Vast.ai. Prices move constantly; see the live price table.

Sources

• blog.hinablue.me/krea2-lora-trainer/
• www.reddit.com/r/StableDiffusion/comments/1vrkd5x/which_platform_shoul
• sanj.dev/post/onetrainer-vs-kohya-ss-vs-ai-toolkit/
• github.com/ostris/ai-toolkit#readme
• github.com/kohya-ss/musubi-tuner#readme
• github.com/kohya-ss/musubi-tuner/blob/main/docs/krea2.md
• github.com/bghira/SimpleTuner#readme
• github.com/Nerogar/OneTrainer/pull/1680
• huggingface.co/heathcliff01/Kaloscope-style-adapter
• github.com/ostris/ai-toolkit/commit/534d462ff622e334e1a65b42884d96d983
• github.com/ostris/ai-toolkit/blob/main/extensions_built_in/diffusion_m
• huggingface.co/adhit-420/Krea-2-PoseControl-LoRA-checkpoints

FAQ

Is 12 GB enough to train a Krea 2 LoRA?

No trainer publishes a Krea 2-specific number. musubi-tuner's general guidance is 12 GB+ for image training, and its fp8 / ConvRot int8 options halve weight VRAM. Whether 12 GB is comfortable for Krea 2 is unknown.

What is the cheapest 12 GB+ GPU to rent?

See the table above and the live price page.

Data updated 2026-10-20. Disclosure: RunPod and Vast.ai links are referral links; ImageLoRA may earn a commission at no cost to you. unknown = no data yet. · Raw data (JSON) · llms.txt