CUDA out of memory. Tried to allocate 22.15 GiB. GPU

[hwxxzz]

Hello , i have an issue with img2vid. i got below error when i try to create a video from an image. Zluda is active. There is no problem with image creating. How can i solve this ?

Console log : !!! Exception during processing!!! CUDA out of memory. Tried to allocate 22.15 GiB. GPU Traceback (most recent call last): File "D:\AI\ComfyUI-Zluda\execution.py", line 151, in recursive_execute output_data, output_ui = get_output_data(obj, input_data_all) File "D:\AI\ComfyUI-Zluda\execution.py", line 81, in get_output_data return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True) File "D:\AI\ComfyUI-Zluda\execution.py", line 74, in map_node_over_list results.append(getattr(obj, func)(slice_dict(input_data_all, i))) File "D:\AI\ComfyUI-Zluda\nodes.py", line 1344, in sample return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) File "D:\AI\ComfyUI-Zluda\nodes.py", line 1314, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, File "D:\AI\ComfyUI-Zluda\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 22, in informative_sample raise e File "D:\AI\ComfyUI-Zluda\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample return original_sample(args, kwargs) # This code helps interpret error messages that occur within exceptions but does not have any impact on other operations. File "D:\AI\ComfyUI-Zluda\comfy\sample.py", line 37, in sample samples = sampler.sample(noise, positive, negative, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 761, in sample return sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 663, in sample return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 650, in sample output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 629, in inner_sample samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 534, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, self.extra_options) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "D:\AI\ComfyUI-Zluda\comfy\k_diffusion\sampling.py", line 137, in sample_euler denoised = model(x, sigma_hat * s_in, extra_args) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 272, in call out = self.inner_model(x, sigma, model_options=model_options, seed=seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 616, in call return self.predict_noise(*args, kwargs) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 619, in predict_noise return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 258, in sampling_function out = calc_cond_batch(model, conds, x, timestep, model_options) File "D:\AI\ComfyUI-Zluda\comfy\samplers.py", line 218, in calc_cond_batch output = model.apply_model(inputx, timestep, c).chunk(batch_chunks) File "D:\AI\ComfyUI-Zluda\comfy\model_base.py", line 97, in apply_model model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, *extra_conds).float() File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(args, kwargs) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, kwargs) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 852, in forward h = forward_timestep_embed(module, h, emb, context, transformer_options, time_context=time_context, num_video_frames=num_video_frames, image_only_indicator=image_only_indicator) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 40, in forward_timestep_embed x = layer(x, context, time_context, num_video_frames, image_only_indicator, transformer_options) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(args, kwargs) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\attention.py", line 789, in forward x = block( File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, kwargs) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, *kwargs) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\attention.py", line 531, in forward n = self.attn1(n, context=context_attn1, value=value_attn1) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(args, kwargs) File "D:\AI\ComfyUI-Zluda\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\attention.py", line 425, in forward out = optimized_attention(q, k, v, self.heads, attn_precision=self.attn_precision) File "D:\AI\ComfyUI-Zluda\comfy\ldm\modules\attention.py", line 357, in attention_pytorch out = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=mask, dropout_p=0.0, is_causal=False) torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 22.15 GiB. GPU

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[ikcikoR]

Buying a bigger GPU or looking into ways to make the VRAM requirements smaller. See if you can do fp8 unet

[hwxxzz]

i have 6800xt. i will check fp8 or i will buy new nvidia gpu :s

[ikcikoR]

i have 6800xt. i will check fp8 or i will new nvidia gpu :s

Since this is about amount of VRAM on your graphics card, 7900 xtx would probably be a better choice because it is way cheaper than RTX 4090 while having the same amount of VRAM. Tho not 100% sure how it compares to 3090 which iirc is the same too