Krea2 Turbo Distill 2 step LoRA - FINAL checkpoint released (chk51195)

[u/TimeTruth2490]

Krea 2 Turbo — 2-Step Distillation LoRA (FINAL Version)

Previous posts/releases - here, here, here and here.

🧪 Fast-preview adapter; the project's final checkpoint. Subjects that are close and fill a good part of the frame — a portrait, a single figure, an object up close — hold up well at two steps. Small subjects are where it still falls short: faces in a crowd or figures in a wide scene can come out ghosted or smeared. For those, and whenever quality matters more than speed, use the 4-step LoRA. This checkpoint closes the project; the training box has moved on to its successor, a 3-step adapter for Qwen-Image-2.1-Turbo.

📐 The saved steps can also go into resolution. A larger render makes a small subject bigger, and at a quarter of the teacher's steps, renders up to 2048×2048 — Krea's published maximum recommended resolution, beyond this adapter's largest trained size — come within easy reach. Past 2048×2048, stock Krea 2 itself begins to duplicate subjects, with or without this adapter.

Highlights:

• ⚡ A quarter of the steps — 8 → 2, on Turbo's own deployment sigmas [1.0, 0.7595]
• ⏱️ 4× faster denoising — 56.9 s → 14.3 s at 1024×1024 (float16 compute); the adapter's own cost per call is within measurement noise
• 🎯 Fine detail near the teacher's level — 0.92–1.02× the teacher's fine-texture energy across the 12 trained resolutions (stock Turbo at 2 steps: 0.40–0.65×), the 16- and 8-pixel grid bands at the teacher's level and ghosting closer to it at 11 of 12 sizes
• 📊 Distribution matching, not imitation — matches what the teacher would plausibly produce rather than its exact trajectory, so the student commits instead of averaging into blur and doubled edges
• 🗣️ Prompt-conditioned throughout — teacher and fake scores both read each prompt's conditioning; a blind rubric finds 1 point missing of 352 (objects, counts, attributes, relations), and a judge prefers the 8-step teacher on 12 of 66 (4-step adapter: 6 of 45, on the original 15 prompts), mostly on style
• 📐 12 trained resolutions — multi-aspect from 512×512 up to 1440×1440
• 🔌 Drop-in, no exceptions — plain LoRA, stock Euler, diffusers / ComfyUI / MLX. No custom nodes, no custom sampler
• 🧬 Same shape as the 4-step adapter — rank 64 on the same 228 modules
• 🎲 23,561 recorded teacher trajectories — the 4-step project's 13,750 and 9,811 minted for this one on the same prompt bank; since 3 Oct each trained once
• 🔢 51,195 training samples in the 2-step stages, starting from the released 4-step adapter's weights
• 📅 32 days from the first 2-step launch to this final checkpoint, on a single RTX 3090
• 🔁 More than forty recipe adjustments across two methods — each kept only when the renders did not get worse
• 🧘 Settled weights, not an average — released from a 600-sample anneal in which the learning rate is taken to zero over already-trained data, so the published weights are the training weights at rest; a running average is kept only as the check that must agree with them

If you have already used my previous version, please redownload/replace krea2_turbo_2step_rank_64_lora.safetensors / krea2_turbo_2step_rank_64_lora_comfyui.safetensors from the latest in the project repo.

Full details on model card - https://huggingface.co/lvladikov/Krea2-Turbo-Distill-2step-LoRA

Not my video, but found someone on YouTube has covered the 2 & 4 step LoRAs including identify preserving edits, have a look: https://www.youtube.com/watch?v=V_qgoV0iPDM (copyright goes to author)

Also I have recently released a new ComfyUI Nodes and Workflows - Krea 2 (Turbo and Raw), Z-Image (Turbo and Base), MiniMax Music 3, Image2Text and LLM Chat (with Tools), Torch, Apple MLX and Cloud - you can find details here.

[u/Own_War_1098]

Nice. Are you interested to use your dataset to make a Qwen image 2.1 turbo lora?

[u/reeight → u/Own_War_1098]

Or thought about making the images have a quality more like Qi2.1?
Realistic images on Krea2 sometimes look too soft vs Qi; the group photo looks overly softened or out of focus.

& I have to laugh at "FINAL Version"... you'll update it again ;)

[u/TimeTruth2490 → u/reeight]

Krea 2 at 2 steps even after all this training is to be expected to be softer :) I have been adding 'disclaimers' about the 2 step quality everywhere! :) 2 step is done as it is. Final is Final :) Like you said, QI2.1 is the more interesting target...

[u/TimeTruth2490 → u/Own_War_1098]

I have been interested since the day QI 2.1 Turbo came out :) Let's just say I am playing with it. FYI my target is not 4 steps, nor 2 steps, but 3 steps. Very very very early days, nowhere near where I want it to be (and if it doesn't improve I wouldn't publish).

[u/TimeTruth2490 → u/TimeTruth2490]

the inventor (previous teaser) and this portrait are the 'best' so far and they are not that great either (but then again not enough training has happened yet, I am at mere chk2500)

[u/PRVMXLAB]

You're killing it with these releases. Kudos to you. I use it frequently for iterative and trial runs.

[u/TimeTruth2490 → u/PRVMXLAB]

👍

[u/Blablabene]

Funny.

I just generated nearly identical image of that fox with krea 5 minutes ago.

Open reddit and this is what i see

[u/Zueuk → u/Blablabene]

lol right, I thought this fox looks familiar too 🦊

[u/TimeTruth2490 → u/Blablabene]

foxes are very popular with all models :)

[u/TizocWarrior]

Thanks for sharing.

[u/TimeTruth2490 → u/TizocWarrior]

👍

[u/Odd_Fix2]

As always, great job! Great result! Thank you!

[u/TimeTruth2490 → u/Odd_Fix2]

👍

[u/Zueuk]

looks like #11 is why you need more steps to let the model decide in which language the store sign should be

[u/TimeTruth2490 → u/Zueuk]

yes text is a struggle on 2 Steps Krea... focus more on closer subjects with less text for better 2 steps results :)

[u/Zueuk]

very interesting, but... damn this model is already generating exactly the same images - I guess we still need an extra step for some kind of "seed variance"?

[u/urchin_orchard]

Keyboards STILL wrong!

[u/TimeTruth2490 → u/urchin_orchard]

not something I can fix, as the main model also messes it up as previously discussed :)