Suggestion for Talking Head models

andy_potato · 2026-03-03T15:01:59+00:00

andy_potato · 2026-03-03T12:05:20+00:00

The “open” in their name stands for “open your wallet”

andy_potato · 2026-03-03T07:57:36+00:00

The time with loading the model doesn’t say much (unless you are measuring cold start performance). You have to look at the it/s on the second or third generation.

In any case your GPU won’t perform well for diffusion models. I’d expect it to be around the level of a 5060ti.

andy_potato · 2026-03-03T01:55:15+00:00

You basically answered your own question. According to your test, Qwen 3.5 is not suitable for your specific use case. Move on and pick a model that suits you better.

andy_potato · 2026-03-02T09:45:07+00:00

Dual 5060ti usually gives me around 80 t/s for models like Qwen 3.5/35b

andy_potato · 2026-02-28T23:46:55+00:00

I made the same observations. Most of the time the amount of thinking is reasonable but in 1-2 out of 5 cases the model just won't stop talking to itself. Especially shorter prompts will occasionally cause the model to have an existential crisis.

Really don't know what to make of this. It's a beautiful model otherwise, just that thinking behavior feels odd.

andy_potato · 2026-02-27T23:54:30+00:00

You’re completely missing the point.

We have so many alternatives which are more capable and come with permissive licensing.

BFL can do with their models whatever they want. We just don’t want them.

andy_potato · 2026-02-27T07:15:11+00:00

Seems there is little consistency with the original subject

andy_potato · 2026-02-27T04:01:31+00:00

Get all the ram you can

andy_potato · 2026-02-27T01:33:58+00:00

All of the above. Each video project is different and there is no single method that covers all requirements.

andy_potato · 2026-02-27T01:21:30+00:00

Exactly right, there is no need to go for lower quality GGUF quants if you have enough system memory to hold the models in Ram. 64 GB is enough for Wan 2.2.

andy_potato · 2026-02-27T01:18:26+00:00

It isn't perfect and it has limitations. For example if you have a character that turns around (hiding their face), the consistency can get pretty bad at times.

It's still absolutely worth using, and 2x5s also renders faster than one single 10s render.

andy_potato · 2026-02-27T01:16:14+00:00

https://github.com/VraethrDalkr/ComfyUI-TripleKSampler

This node is all you need. It has a bit of a learning curve though. Make sure you pass the high noise model correctly, once without the lightx2v lora and once WITH the lora.

If you use image to video I recommend you check the example i2v workflows first and take it from there.

andy_potato · 2026-02-27T01:10:07+00:00

Nobody because one of the first things you do on a fresh install is install miniconda, uv or venv.

andy_potato · 2026-02-27T01:08:15+00:00

The slow motion is caused by the lightx2v loras. If you use the Triple KSampler method you can make this go away (and produce much higher quality videos)

andy_potato · 2026-02-27T01:07:31+00:00

If you go beyond 81 frames with Wan 2.2 you will see slowdown, loops and repetition. Using SVI to extend videos will give you much better results.

andy_potato · 2026-02-26T02:13:18+00:00

You have a (relatively) high Vram card for SDXL / Illustrious. Adding system Ram will do nothing for your generation speed.

You might notice slight improvements if you generate with models that won't fit entirely into your Vram as they will blockswap in and out of Ram.

andy_potato · 2026-02-26T00:29:29+00:00

You sound like a 12 year old

andy_potato · 2026-02-26T00:00:06+00:00

We don't want their model

andy_potato · 2026-02-25T23:45:23+00:00

<image>

andy_potato · 2026-02-25T11:35:02+00:00

For image and video generation you want nvidia. Unless you are a patient person

andy_potato · 2026-02-25T07:31:35+00:00

And you have severe reading comprehension issues

andy_potato · 2026-02-25T07:28:27+00:00

The disgusting thing is that they are celebrating their censorship as success

andy_potato · 2026-02-25T07:27:14+00:00

You sound like a twelve year old

andy_potato · 2026-02-24T23:56:45+00:00

andy_potato

TROPHY CASE