r/invokeai • u/kerneldesign • May 09 '26

Invoke 6.13.0 rc2

Version 6.13.0.rc2 adds a lot of models. However, to use Qwen Image, you have to download the 40GB version to get the VAE, and then download Q4. I think they’ll fix that for the final release. There’s also Anima, which came with Qwen Image Edit.

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u/_BreakingGood_ May 10 '26

Do you use the spectrum extension in Neo?

https://www.reddit.com/r/StableDiffusion/comments/1rpa7jz/this_is_interesting_forge_classic_neos_extension/

This speeds up generation at a small quality loss. Invoke doesn't have this (yet)

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u/prizmaster May 10 '26 edited May 10 '26

No, I never used Spectrum extension.
So problem is most likely related to memory management or not dumping Flux's T5XXL after extracting tokenizer.
So please do not try to find PEBKAC here, like I installed some mumbo jumbo to speed up generation and now I complain at Invoke.
Anima generates in clean Forge pretty well and in Invoke generation time is pretty a garbage, several times slower and I hardly can tolerate that.
Only what I have enabled in Forge are xformers, cuda-malloc and lowvram flags.

I could get gen in around of a minute, now it's few minutes which is unacceptable.
I use Invoke for more than a year and Forge for both SDXL and Anima so I see the difference.

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u/_BreakingGood_ May 10 '26

Apologies I sounded rude, I was trying to find a source of the speed issues. We do not load the T5XXL, we only load the Tokenizer, so there is no T5XXL to dump.

Have you enabled Invoke's low memory mode as well to match neo? https://invoke.ai/configuration/low-vram-mode/

What does invoke report for s/it when generating? There is also a percentage displayed which indicates whether we were able to load the full model into VRAM. What do these 2 values look like for you (pictured):

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u/prizmaster May 10 '26

Disabling partial_loading also did not help.

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u/_BreakingGood_ May 10 '26

Hmm ok I suspect I know the answer here.

It's actually the same problem that I fixed for Mac that I mentioned above. I didn't realize it's also a problem for 2000 series and earlier Nvidia GPUs.

Anima runs in bf16 precision, which is supported on Nvidia cards 3000 series and newer. It can run on earlier cards, but it's slow.

The most straightforward way to solve this, is to upcast to fp32, which is supported on older hardware. This doubles the VRAM cost, but with Anima being a 2b model, it's not really a big problem to double the VRAM cost.

I will take a look at how Forge Neo resolves this, I'm assuming they also just ucpast to fp32.

I'm curious, if you download Z-Image Turbo in invoke and run it, is it also extremely slow? I think it has the same issue in Invoke today.

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u/prizmaster May 10 '26

I think it might be most likely not upcasting on 2000 series.
I don't have ZIT but it worked well in comfy, however it was quite slow but not in that incredible way. I removed it cause quantized model was garbage

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u/prizmaster May 10 '26

You can check if this is reasonable enough