[bug]: Flux (GGUF) broken on MPS, updating PyTorch fixes

[Vargol]

Is there an existing issue for this problem?

• I have searched the existing issues

Install method

Manual

Operating system

macOS

GPU vendor

Apple Silicon (MPS)

GPU model

M3

GPU VRAM

24GB

Version number

6.11.0

Browser

Safari

System Information

{
"version": "6.11.0",
"dependencies": {
"absl-py" : "2.3.1",
"accelerate" : "1.12.0",
"annotated-types" : "0.7.0",
"anyio" : "4.12.0",
"attrs" : "25.4.0",
"bidict" : "0.23.1",
"blake3" : "1.0.8",
"certifi" : "2025.11.12",
"cffi" : "2.0.0",
"charset-normalizer" : "3.4.4",
"click" : "8.3.1",
"coloredlogs" : "15.0.1",
"compel" : "2.1.1",
"contourpy" : "1.3.3",
"CUDA" : "N/A",
"cycler" : "0.12.1",
"Deprecated" : "1.3.1",
"diffusers" : "0.36.0",
"dnspython" : "2.8.0",
"dynamicprompts" : "0.31.0",
"einops" : "0.8.1",
"fastapi" : "0.118.3",
"fastapi-events" : "0.12.2",
"filelock" : "3.20.1",
"flatbuffers" : "25.12.19",
"fonttools" : "4.61.1",
"fsspec" : "2025.12.0",
"gguf" : "0.17.1",
"h11" : "0.16.0",
"hf-xet" : "1.2.0",
"httpcore" : "1.0.9",
"httptools" : "0.7.1",
"httpx" : "0.28.1",
"huggingface-hub" : "0.36.0",
"humanfriendly" : "10.0",
"idna" : "3.11",
"importlib_metadata" : "8.7.1",
"InvokeAI" : "6.11.0",
"jax" : "0.7.1",
"jaxlib" : "0.7.1",
"Jinja2" : "3.1.6",
"kiwisolver" : "1.4.9",
"MarkupSafe" : "3.0.3",
"matplotlib" : "3.10.8",
"mediapipe" : "0.10.14",
"ml_dtypes" : "0.5.4",
"mpmath" : "1.3.0",
"networkx" : "3.6.1",
"numpy" : "1.26.4",
"onnx" : "1.16.1",
"onnxruntime" : "1.19.2",
"opencv-contrib-python": "4.11.0.86",
"opt_einsum" : "3.4.0",
"packaging" : "25.0",
"picklescan" : "0.0.33",
"pillow" : "12.0.0",
"pip" : "24.0",
"prompt_toolkit" : "3.0.52",
"protobuf" : "4.25.8",
"psutil" : "7.2.0",
"pycparser" : "2.23",
"pydantic" : "2.12.5",
"pydantic-settings" : "2.12.0",
"pydantic_core" : "2.41.5",
"pyparsing" : "3.3.1",
"PyPatchMatch" : "1.0.2",
"python-dateutil" : "2.9.0.post0",
"python-dotenv" : "1.2.1",
"python-engineio" : "4.13.0",
"python-multipart" : "0.0.21",
"python-socketio" : "5.16.0",
"PyWavelets" : "1.9.0",
"PyYAML" : "6.0.3",
"regex" : "2025.11.3",
"requests" : "2.32.5",
"safetensors" : "0.7.0",
"scipy" : "1.16.3",
"semver" : "3.0.4",
"sentencepiece" : "0.2.0",
"setuptools" : "65.5.0",
"simple-websocket" : "1.1.0",
"six" : "1.17.0",
"sounddevice" : "0.5.3",
"spandrel" : "0.4.1",
"starlette" : "0.48.0",
"sympy" : "1.14.0",
"tokenizers" : "0.22.1",
"torch" : "2.7.1",
"torchsde" : "0.2.6",
"torchvision" : "0.22.1",
"tqdm" : "4.67.1",
"trampoline" : "0.1.2",
"transformers" : "4.57.3",
"typing-inspection" : "0.4.2",
"typing_extensions" : "4.15.0",
"urllib3" : "2.6.2",
"uvicorn" : "0.40.0",
"uvloop" : "0.22.1",
"watchfiles" : "1.1.1",
"wcwidth" : "0.2.14",
"websockets" : "15.0.1",
"wrapt" : "2.0.1",
"wsproto" : "1.3.2",
"zipp" : "3.23.0"
},
"config": {
"schema_version": "4.0.2",
"legacy_models_yaml_path": null,
"host": "127.0.0.1",
"port": 9090,
"allow_origins": [],
"allow_credentials": true,
"allow_methods": [""],
"allow_headers": [""],
"ssl_certfile": null,
"ssl_keyfile": null,
"log_tokenization": false,
"patchmatch": true,
"models_dir": "models",
"convert_cache_dir": "models/.convert_cache",
"download_cache_dir": "models/.download_cache",
"legacy_conf_dir": "configs",
"db_dir": "databases",
"outputs_dir": "/Users/davidburnett/invokeai/outputs",
"custom_nodes_dir": "nodes",
"style_presets_dir": "style_presets",
"workflow_thumbnails_dir": "workflow_thumbnails",
"log_handlers": ["console"],
"log_format": "color",
"log_level": "info",
"log_sql": false,
"log_level_network": "warning",
"use_memory_db": false,
"dev_reload": false,
"profile_graphs": false,
"profile_prefix": null,
"profiles_dir": "profiles",
"max_cache_ram_gb": null,
"max_cache_vram_gb": null,
"log_memory_usage": false,
"model_cache_keep_alive_min": 0,
"device_working_mem_gb": 3,
"enable_partial_loading": false,
"keep_ram_copy_of_weights": false,
"ram": null,
"vram": null,
"lazy_offload": true,
"pytorch_cuda_alloc_conf": null,
"device": "mps",
"precision": "bfloat16",
"sequential_guidance": false,
"attention_type": "torch-sdp",
"attention_slice_size": "auto",
"force_tiled_decode": false,
"pil_compress_level": 1,
"max_queue_size": 10000,
"clear_queue_on_startup": false,
"allow_nodes": null,
"deny_nodes": null,
"node_cache_size": 512,
"hashing_algorithm": "blake3_single",
"remote_api_tokens": null,
"scan_models_on_startup": false,
"unsafe_disable_picklescan": false,
"allow_unknown_models": true
},
"set_config_fields": [
"device", "keep_ram_copy_of_weights", "outputs_dir", "precision",
"attention_type", "legacy_models_yaml_path"
]
}

What happened

Reporting the results of this discord conversation.
https://discord.com/channels/1020123559063990373/1149506274971631688/1468200636540653604

Using Flux1.dev (Q8 GGUF tested) generating a image in the Linear UI results in a noise image on a MacOS computer using MPS

Updating torch and torchvision to the current production versions (2.10.0 and 0.25.0 respectively) resolves the issue and Flux works again (ZiT and Klein tested too and still work).

What you expected to happen

Flux.1 dev should generate a image that isn't just noise,

How to reproduce the problem

Generate a image using a FLUX.1 [dev] model using the preferred settings and the with appropriate components...

Additional context

No response

Discord username

Vargol