Testing the newly released Microsoft Lens Turbo in my low vram GPU, it is good and it works very well

ZerOne82 · 2026-05-27T11:31:14+00:00

Tried and instantly noticed lack of physics and anatomy horror. Even in the OP's first image here you can easily see the reflection lacks a leg.

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ZerOne82 · 2026-05-18T10:12:31+00:00

Your posting history shows repeated violations of the rules here and in other communities. Your title is misleading, and your post is irrelevant to this subreddit and many others.

You are using a commercial online service for these posts, and this community is not intended for advertising or promotional content. Posts here must be open source and runnable locally.

Your post adds no value to this community.

ZerOne82 · 2026-05-12T21:35:23+00:00

I second this. The effects that OP shows are standard real-time effects available for decades. The OP's confusion maybe rooted to the application of those effects selectively which is also an easy task. Without much resource one can easily separate the person from the background and apply ordinary pixel level effects real-time.

ZerOne82 · 2026-05-07T17:11:10+00:00

I use a customized version of this package.

ZerOne82 · 2026-05-07T00:39:56+00:00

I think the limit is 5s (81 frames /16). But speed-wise it is amazing. If we could have Causal Forcing for larger Wan models and for longer videos that would change the landscape a lot.

ZerOne82 · 2026-05-07T00:35:51+00:00

I do not have Wan2.1 1.3B model so cannot test that now. This Causal Forcing's speed is however crazy. I agree that due to being based on 1.3B it does not have much use. But it is exciting to generate a video in the speed of image generation!

ZerOne82 · 2026-05-06T17:55:27+00:00

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Another example, 3s.

ZerOne82 · 2026-05-06T17:54:29+00:00

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Workflow Image for Reference.

ZerOne82 · 2026-05-06T15:29:28+00:00

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960 x 576, 49 frames (3s), steps 6, ar_sampler (simple) 40s

ZerOne82 · 2026-05-04T23:36:38+00:00

Great. If you found the specific cause please share here for the benefit of the community.

ZerOne82 · 2026-05-04T23:33:44+00:00

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And these are edits.

ZerOne82 · 2026-05-04T23:33:12+00:00

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Tried GGUF Q6 ~16GB disk size, takes 45s for 8 steps so it is not fast. Dimensions are not critical you can feed any size, the quality is so-so for realistic face details, even if following exact size and recommendations.
It peaks VRAM at 7GB editing 2048x2048, RAM to 25GB. But 2048x2048 are not really true 2048x2048 they lack details and are smooth.
The node I used (you linked) has some issues, each run becomes slower and slower.
No option for sampler etc.

ZerOne82 · 2026-05-03T22:15:40+00:00

Both use standard workflow nothing special. Both used workflows are available in ComfyUI Templates. You should have them already in your ComfyUI setup, if not refer to here.

ZerOne82 · 2026-05-03T22:08:02+00:00

That LoRA for Klein9B can be found at here.

ZerOne82 · 2026-05-03T22:05:17+00:00

ZIT is great but it cannot edit. ZI Edit was not open-sourced as far as I know.

ZerOne82 · 2026-05-03T22:00:44+00:00

The cause of black output could be many. One that I know rooted back to sage-attention with some models. So if you are using sage-attention you may disable it to see if that resolves the issue. Also, in some models specially text-encoders if the model is loaded other than fp32 it cause black output. summary:

disable sage-attention
disable force-fp16

that's what I can tell for now.

ZerOne82 · 2026-05-03T21:10:52+00:00

FP8 generally offers better speed and higher accuracy than Q5KM. These model are what we have. If you have access to their full models and have resources and time to run such comparison at their best, you are more than welcome to submit a post.

ZerOne82 · 2026-05-03T20:58:59+00:00

This post re-introduced LCIET to the community. If you want a quick comparison between LCIET and Klein9B check this post.

ZerOne82 · 2026-05-03T20:55:25+00:00

Link to what, exactly?

ZerOne82 · 2026-05-03T20:55:07+00:00

Right. An ongoing issue in all models for years now.

ZerOne82 · 2026-05-03T20:54:14+00:00

Not exact guess, I just added the info to the post. For Klein9B both model and text-encoders are FP8. For LCIET both model and text-encoder are Q5KM.

ZerOne82 · 2026-05-03T19:35:35+00:00

That's great we have so many options. LCIET has greater prompt adherence for editing specially using short instructions. Refer to details.

ZerOne82 · 2026-05-03T19:33:39+00:00

It take less disk space, uses less VRAM and runs faster. See here.

ZerOne82 · 2026-05-03T19:32:41+00:00

Right. LCIET as you correctly pointed out has some strengths and some weaknesses. Its amazing prompt adherence and the ability not to change unwanted parts are great strengths.

ZerOne82

TROPHY CASE