RuntimeError: Expected all tensors to be on the same device

[qteen1995]

error message

RuntimeError: Expected all tensors to be on the same device, but got index is on cuda:0, different from other tensors on cpu (when checking argument in method wrapper_CUDA__index_select)

OS: Windows 10/11
Python: 3.10.6
PyTorch: 2.8.0+cu128
GPU: NVIDIA GeForce RTX 3080 (20GB VRAM)
Project version: f2.0.1v1.10.1-1.10.1 (commit: 7f9b6a6)
Startup parameters: --cuda-malloc --always-low-vram

[qteen1995]

venv "E:\chromaforge\venv\Scripts\Python.exe"
fatal: No names found, cannot describe anything.
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: f2.0.1v1.10.1-1.10.1
Commit hash: 7f9b6a6
Installing requirements
Launching Web UI with arguments: --ckpt-dir 'E:\sd-webui-aki-v\models\Stable-diffusion' --hypernetwork-dir 'E:\sd-webui-aki-v\models\hypernetworks' --embeddings-dir 'E:\sd-webui-aki-v\models\embeddings' --lora-dir 'E:\sd-webui-aki-v\models\Lora' --vae-dir 'E:\sd-webui-aki-v\models\VAE' --text-encoder-dir 'E:\sd-webui-aki-v\models\text_encoder' --listen --port 7878 --cuda-malloc --always-low-vram
Using cudaMallocAsync backend.
Total VRAM 20480 MB, total RAM 32661 MB
pytorch version: 2.8.0+cu128
Set vram state to: LOW_VRAM
Device: cuda:0 NVIDIA GeForce RTX 3080 : cudaMallocAsync
VAE dtype preferences: [torch.bfloat16, torch.float32] -> torch.bfloat16
CUDA Using Stream: False
Using pytorch cross attention
Using pytorch attention for VAE
Directory tmp/gradio_themes does not exist. No new themes will be added.
ControlNet preprocessor location: E:\chromaforge\models\ControlNetPreprocessor
2025-12-07 15:32:49,791 - ControlNet - INFO - ControlNet UI callback registered.
Model selected: {'checkpoint_info': {'filename': 'E:\sd-webui-aki-v\models\Stable-diffusion\z_image_de_turbo_v1_bf16.safetensors', 'hash': '04dfda4c'}, 'additional_modules': [], 'unet_storage_dtype': None, 'z_transformer_dtype': 'Automatic', 'z_vae_dtype': 'Automatic', 'z_text_encoder_dtype': 'Automatic'}
Using online LoRAs in FP16: False
Running on local URL: http://0.0.0.0:7878

To create a public link, set share=True in launch().
Startup time: 35.7s (prepare environment: 7.9s, launcher: 0.5s, import torch: 13.7s, initialize shared: 0.3s, other imports: 0.8s, list SD models: 0.1s, load scripts: 3.3s, create ui: 3.2s, gradio launch: 5.7s).
Environment vars changed: {'stream': False, 'inference_memory': 1024.0, 'pin_shared_memory': False}
[GPU Setting] You will use 95.00% GPU memory (19455.00 MB) to load weights, and use 5.00% GPU memory (1024.00 MB) to do matrix computation.
Model selected: {'checkpoint_info': {'filename': 'E:\sd-webui-aki-v\models\Stable-diffusion\z_image_turbo_bf16.safetensors', 'hash': '04a63cf9'}, 'additional_modules': [], 'unet_storage_dtype': None, 'z_transformer_dtype': 'Automatic', 'z_vae_dtype': 'Automatic', 'z_text_encoder_dtype': 'Automatic'}
Using online LoRAs in FP16: False
Model selected: {'checkpoint_info': {'filename': 'E:\sd-webui-aki-v\models\Stable-diffusion\z_image_turbo_bf16.safetensors', 'hash': '04a63cf9'}, 'additional_modules': ['E:\sd-webui-aki-v\models\VAE\Flux-ae.safetensors'], 'unet_storage_dtype': None, 'z_transformer_dtype': 'Automatic', 'z_vae_dtype': 'Automatic', 'z_text_encoder_dtype': 'Automatic'}
Using online LoRAs in FP16: False
Model selected: {'checkpoint_info': {'filename': 'E:\sd-webui-aki-v\models\Stable-diffusion\z_image_turbo_bf16.safetensors', 'hash': '04a63cf9'}, 'additional_modules': ['E:\sd-webui-aki-v\models\VAE\Flux-ae.safetensors', 'E:\sd-webui-aki-v\models\text_encoder\qwen_3_4b.safetensors'], 'unet_storage_dtype': None, 'z_transformer_dtype': 'Automatic', 'z_vae_dtype': 'Automatic', 'z_text_encoder_dtype': 'Automatic'}
Using online LoRAs in FP16: False
Loading Model: {'checkpoint_info': {'filename': 'E:\sd-webui-aki-v\models\Stable-diffusion\z_image_turbo_bf16.safetensors', 'hash': '04a63cf9'}, 'additional_modules': ['E:\sd-webui-aki-v\models\VAE\Flux-ae.safetensors', 'E:\sd-webui-aki-v\models\text_encoder\qwen_3_4b.safetensors'], 'unet_storage_dtype': None, 'z_transformer_dtype': 'Automatic', 'z_vae_dtype': 'Automatic', 'z_text_encoder_dtype': 'Automatic'}
[Unload] Trying to free all memory for cuda:0 with 0 models keep loaded ... Done.
DEBUG: Loading Z-Image model from preset
[Z-Image] Detected ComfyUI format, converting to Diffusers format...
[Z-Image] Converted 108 keys, split 34 fused QKV weights
Working with z of shape (1, 16, 32, 32) = 16384 dimensions.
DEBUG: Loaded Z-Image components: ['scheduler', 'text_encoder', 'tokenizer', 'transformer', 'vae']
K-Model Created: {'storage_dtype': torch.bfloat16, 'computation_dtype': torch.bfloat16}
Calculating sha256 for E:\sd-webui-aki-v\models\Stable-diffusion\z_image_turbo_bf16.safetensors: 2407613050b809ffdff18a4ac99af83ea6b95443ecebdf80e064a79c825574a6
Model loaded in 37.1s (unload existing model: 0.2s, forge model load: 27.0s, calculate hash: 9.9s).
Skipping unconditional conditioning when CFG = 1. Negative Prompts are ignored.
All loaded to GPU.
Moving model(s) has taken 0.01 seconds
Traceback (most recent call last):
File "E:\chromaforge\modules_forge\main_thread.py", line 30, in work
self.result = self.func(*self.args, **self.kwargs)
File "E:\chromaforge\modules\txt2img.py", line 132, in txt2img_function
processed = processing.process_images(p)
File "E:\chromaforge\modules\processing.py", line 848, in process_images
res = process_images_inner(p)
File "E:\chromaforge\modules\processing.py", line 977, in process_images_inner
p.setup_conds()
File "E:\chromaforge\modules\processing.py", line 1636, in setup_conds
super().setup_conds()
File "E:\chromaforge\modules\processing.py", line 506, in setup_conds
self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)
File "E:\chromaforge\modules\processing.py", line 475, in get_conds_with_caching
cache[1] = function(shared.sd_model, required_prompts, steps, hires_steps, shared.opts.use_old_scheduling)
File "E:\chromaforge\modules\prompt_parser.py", line 262, in get_multicond_learned_conditioning
learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps, hires_steps, use_old_scheduling)
File "E:\chromaforge\modules\prompt_parser.py", line 189, in get_learned_conditioning
conds = model.get_learned_conditioning(texts)
File "E:\chromaforge\venv\lib\site-packages\torch\utils_contextlib.py", line 120, in decorate_context
return func(*args, **kwargs)
File "E:\chromaforge\backend\diffusion_engine\zimage.py", line 480, in get_learned_conditioning
outputs = text_encoder(
File "E:\chromaforge\venv\lib\site-packages\torch\nn\modules\module.py", line 1773, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "E:\chromaforge\venv\lib\site-packages\torch\nn\modules\module.py", line 1784, in _call_impl
return forward_call(*args, **kwargs)
File "E:\chromaforge\venv\lib\site-packages\transformers\utils\generic.py", line 1072, in wrapper
outputs = func(self, *args, **kwargs)
File "E:\chromaforge\venv\lib\site-packages\transformers\models\qwen3\modeling_qwen3.py", line 371, in forward
inputs_embeds = self.embed_tokens(input_ids)
File "E:\chromaforge\venv\lib\site-packages\torch\nn\modules\module.py", line 1773, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "E:\chromaforge\venv\lib\site-packages\torch\nn\modules\module.py", line 1784, in _call_impl
return forward_call(*args, **kwargs)
File "E:\chromaforge\venv\lib\site-packages\torch\nn\modules\sparse.py", line 192, in forward
return F.embedding(
File "E:\chromaforge\venv\lib\site-packages\torch\nn\functional.py", line 2546, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected all tensors to be on the same device, but got index is on cuda:0, different from other tensors on cpu (when checking argument in method wrapper_CUDA__index_select)
Expected all tensors to be on the same device, but got index is on cuda:0, different from other tensors on cpu (when checking argument in method wrapper_CUDA__index_select)

[maybleMyers]

I think it was from always-low-vram, I tried it with that and it seems to work now, update merged. Cool gpu btw!

[obs945]

I encountered same issue but my is mac silicon m1

RuntimeError: Expected all tensors to be on the same device, but found at least two devices, mps:0 and cpu!
Expected all tensors to be on the same device, but found at least two devices, mps:0 and cpu!

Startup parameters: --skip-torch-cuda-test --use-cpu all