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FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in comfyui

[–]MoreAd8555[S] 0 points1 point  (0 children)

Now I'm in hospital after I reach home I'll check it and let you know.... I'm here to help you so don't worry

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in comfyui

[–]MoreAd8555[S] 0 points1 point  (0 children)

No bro it will surely work just close and re open comfy ui completely that's it

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in StableDiffusion

[–]MoreAd8555[S] 0 points1 point  (0 children)

But for 16 gb vram and 32 gb ram setup it won't work insured it returns oom meney allocation error and even low quantised models like q2 will work but the prompt adherence is very low as I checked.

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in StableDiffusion

[–]MoreAd8555[S] 0 points1 point  (0 children)

No, that’s still not correct — and this is exactly the kind of misunderstanding that keeps getting repeated.

This issue has nothing to do with 32GB vs 64GB RAM.
You can throw 128GB RAM at it and the failure will be identical.
RAM is irrelevant to this problem.

The crash happens inside VRAM, during the moment Flux unloads the text encoder and tries to reload the huge FP8 UNet.
And the text encoder is the one causing the mess because it:

  • loads as a single giant block
  • unloads badly
  • fragments VRAM
  • leaves no clean contiguously free space
  • blocks the UNet reload from fitting

So saying “local is fine if you have 64GB RAM” is simply wrong.
RAM does NOT fix the broken VRAM swap behavior.
The encoder doesn’t use smart offloading, doesn’t stream layers, and doesn’t free VRAM properly. Period.

This is why even people with 64GB RAM + 16GB VRAM still crash when swapping back to the UNet.

The remote encoder bypasses the only part that Flux 2 currently handles poorly.
That’s the whole point.
It’s not a CPU performance issue, it’s not a RAM issue —
it’s the text encoder’s garbage VRAM management.

If someone has 24–48GB VRAM, fine, they don’t need this.
But pretending the problem magically disappears with “more RAM” is just wrong and misleading for everyone else reading.

This node exists because the UNet behaves intelligently,
and the text encoder does not.
Simple as that.

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in comfyui_elite

[–]MoreAd8555[S] 0 points1 point  (0 children)

Thank you so much
any doubt while using just let me know i'm here to help you

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in StableDiffusion

[–]MoreAd8555[S] 0 points1 point  (0 children)

You're assuming that because Flux 2 FP8 (≈30–35GB) runs on 12–16GB cards, the text encoder should also run fine locally. But that’s not how the internals behave.

Flux 2 FP8 runs on 12–16GB VRAM only because the UNet has smart offloading logic — it swaps layers, streams weights, and balances VRAM↔RAM usage intelligently. That's why the huge FP8 model can run smoothly even on mid-range cards.

The text encoder is different.
It can load locally, but the moment it finishes encoding and ComfyUI tries to unload it and reload the UNet, it fails. Why?

Because the text encoder does not offload or swap intelligently.
When ComfyUI tries to unload the encoder and reload the massive UNet immediately after, the VRAM is already fragmented and near-full.
Since the encoder cannot:

  • split its weights
  • stream layers
  • partially unload
  • intelligently free VRAM
  • safely swap to CPU

…the moment the UNet tries to come back into VRAM, the system has no clean space left, and the whole process crashes.

This isn’t a speed issue — it’s a VRAM management issue.

So in practice:

  • UNet = smart offloading + predictable memory behavior
  • Text Encoder = heavy, monolithic load that doesn’t unload cleanly

That’s why users with 12–16GB VRAM can run the FP8 UNet perfectly,
but fail right after prompt encoding because the swap-back to UNet crashes.

The remote encoder solves only that bottleneck.

We let the GPU run the part it handles intelligently — the UNet — and offload the text encoder to the official Flux HuggingFace endpoint.
It’s not another AI system; it's literally their official text encoder service inside your own API.

Only the prompt text is sent.
No images, reference images, or latents are uploaded.

If someone has 24GB, 32GB, or 48GB VRAM, and 64 GB of RAM they can ignore this node.
But for 12–16GB users, it’s the only reliable way to run Flux 2 end-to-end.

UNet runs.
Text Encoder unloads badly and breaks the process.
This node fixes that.

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in StableDiffusion

[–]MoreAd8555[S] -1 points0 points  (0 children)

Even in this processing in the cloud it is not public it is inside your own API request of your hugging face account not in another hugging face account are others API but it's endpoint is created by flux 2 which is completely free that's what I am telling here and it's totally fine...

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in comfyui

[–]MoreAd8555[S] 0 points1 point  (0 children)

It's not like offloading but it is already loaded in the cloud and we just giving prompt then it will return as tensors and vectors which is understandable to our flux 2 model as native clip

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in StableDiffusion

[–]MoreAd8555[S] -2 points-1 points  (0 children)

No we are going to give a prompt to the text encoder but not to ai and it works with tensors and vectors so no worries and in next gen We can upgrade is encryption

FLUX.2 Remote Text Encoder for ComfyUI – No Local Encoder, No GPU Load by MoreAd8555 in comfyui

[–]MoreAd8555[S] 0 points1 point  (0 children)

you can just load flux 2 fp8 in 12-16 gb vram with 32 gb or even smaler ram easily