# Kandinsky 6, mirrored The files WAS Node Suite runs Kandinsky 6 with, laid out as ComfyUI's own `models` folder: `diffusion_models/` for Load Diffusion Model, `text_encoders/` for DualCLIPLoader with type `kandinsky5`, `vae/` for Load VAE and Kandinsky 6 Audio VAE Loader. The text encoders and the audio VAE are byte for byte the upstream file named beside them; the transformers are ComfyUI quantisations of the upstream file, described below. | File | Upstream | Licence | |---|---|---| | `diffusion_models/kandinsky6_lite_distill_5s_int8_convrot.safetensors` | int8 ConvRot of [kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers) at `efbaeb9961770cc82fece5b9cb2197049d8c983c`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_lite_distill_5s_w6a8.safetensors` | W6A8 of [kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers) at `efbaeb9961770cc82fece5b9cb2197049d8c983c`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_lite_5s_int8_convrot.safetensors` | int8 ConvRot of [kandinskylab/Kandinsky-6.0-Lite-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Lite-5s-Diffusers) at `5686616f04318cbec7b0a4978b4ff1697395de15`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_lite_5s_w6a8.safetensors` | W6A8 of [kandinskylab/Kandinsky-6.0-Lite-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Lite-5s-Diffusers) at `5686616f04318cbec7b0a4978b4ff1697395de15`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_pro_distill_5s_int8_convrot.safetensors` | int8 ConvRot of [kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers) at `1018d5828716e8bea3de99609f45c924de9c5564`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_pro_distill_5s_w6a8.safetensors` | W6A8 of [kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers) at `1018d5828716e8bea3de99609f45c924de9c5564`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_pro_5s_int8_convrot.safetensors` | int8 ConvRot of [kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers) at `295ca976810e318fb45c870ba4fc72c9a37fd548`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `diffusion_models/kandinsky6_pro_5s_w6a8.safetensors` | W6A8 of [kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers) at `295ca976810e318fb45c870ba4fc72c9a37fd548`, `transformer/diffusion_pytorch_model.safetensors` | MIT, Kandinsky Lab: `diffusion_models/LICENSE-Kandinsky6` | | `text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors` | [Comfy-Org/Qwen-Image_ComfyUI](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI) at `1f12b17be14c89b026c51a91d67c32f84bb047bc`, `split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors`, Comfy-Org's fp8 repackaging of [Qwen/Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) | Apache-2.0, Alibaba Cloud: `text_encoders/LICENSE-Qwen2.5-VL` | | `text_encoders/clip_l.safetensors` | [Comfy-Org/HunyuanVideo_repackaged](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged) at `533a43813f01517d9e624f9e824a85bb94094120`, `split_files/text_encoders/clip_l.safetensors`, the text tower of [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) | MIT, OpenAI: `text_encoders/LICENSE-CLIP` | | `vae/kandinsky6_audio_vae.safetensors` | [kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers](https://huggingface.co/kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers) at `efbaeb9961770cc82fece5b9cb2197049d8c983c`, `audio_vae/diffusion_pytorch_model.safetensors` | **CC BY-NC 4.0, non-commercial**, and MIT: see below | ## The transformers are ComfyUI quantisations The Kandinsky 6 transformers are held here only as ComfyUI quantised checkpoints, made from the upstream file with comfy-kitchen's own quantisers and loaded by ComfyUI's Load Diffusion Model as they are. | Suffix | Format | |---|---| | `_int8_convrot` | `int8_tensorwise` with ConvRot rotation, group 256, one scale per output row | | `_w6a8` | `w6a8_int8`, 6-bit weights in groups of 32 with ConvRot rotation, group 256, run with int8 activations | Quantised: the query, key, value and output projections and both feed-forward weights of every transformer block whose input width is a multiple of 256. Every other tensor is bfloat16. On Lite the audio stream is 896 wide, so its block weights stay bfloat16 too. Kandinsky-6.0-Pro-5s-Diffusers is gated on Hugging Face behind an access form; its licence is MIT, the same as every other Kandinsky 6 transformer here. Source transformers, SHA-256: f84ea3266560bbd1f203a874b8cee43e080073820facaf3306cab8fae2798a97 kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers@1018d58287 transformer b1b52668561d9138d93bb4da13c9999e615bf569be9f8cf65732d54652447f53 kandinskylab/Kandinsky-6.0-Lite-distill-5s-Diffusers@efbaeb9961 transformer 1550090ca56fed8c75dda0d30f8aa7b46775e8e1ebb086b70ad532e40eb878f9 kandinskylab/Kandinsky-6.0-Lite-5s-Diffusers@5686616f04 transformer f0568ea71b9d754b9538808fc61662c22123fd852e9f7c667f6150ed5f725967 kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers@295ca97681 transformer ## SHA-256 b3fb6f0bd38077e769ef947555927a25d585269903328417bf8c6da8dda277c0 diffusion_models/kandinsky6_lite_distill_5s_int8_convrot.safetensors e936e403761efd07463bc96a4d6608a8014399243c76a8b249d6e3b7be9398e9 diffusion_models/kandinsky6_lite_distill_5s_w6a8.safetensors f6b8a302c99116ee1273a062b8978e10437a6b06f98c71f1c5ba49ecb485aa4c diffusion_models/kandinsky6_lite_5s_int8_convrot.safetensors 375b16bd1f3981806d7f9513978f0c1e0a460d074d080fe1f267c189cbb895f4 diffusion_models/kandinsky6_lite_5s_w6a8.safetensors 8b96fc841b9ecd1d96218b70ecffd846ba8b620fa24d087fc99a547fbdc4edf9 diffusion_models/kandinsky6_pro_distill_5s_int8_convrot.safetensors d26c82be04d5e2d97f4bcf184f0af09768f3af92ade3b7fff52ee181f0a0b968 diffusion_models/kandinsky6_pro_distill_5s_w6a8.safetensors e21a0a4eeab4c25491d30b0af05358830cdd556ffe434c0866e41866c2ad694b diffusion_models/kandinsky6_pro_5s_int8_convrot.safetensors 30ad0006e81bec43d00afa0c6c97b64dd94b47481287ec8b97d5e91a0ecab815 diffusion_models/kandinsky6_pro_5s_w6a8.safetensors cb5636d852a0ea6a9075ab1bef496c0db7aef13c02350571e388aea959c5c0b4 text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd text_encoders/clip_l.safetensors dfccdf9d0d8d3de270a23b097400f21adb91f4ec683bdc26369cb65b08a5af87 vae/kandinsky6_audio_vae.safetensors ## The audio VAE is non-commercial `vae/kandinsky6_audio_vae.safetensors` holds three parts, under the keys they load from: | Keys | What it is | Origin | Licence | |---|---|---|---| | `vae.` | The 44.1 kHz mel autoencoder | `ext_weights/v1-44.pth` from [hkchengrex/MMAudio](https://huggingface.co/hkchengrex/MMAudio), Sony Research Inc., with its weight normalisation folded into the stored weights | CC BY-NC 4.0: `vae/LICENSE-MMAudio-weights` | | `vocoder.` | BigVGAN v2, 44.1 kHz, 128 bands, 512x | `bigvgan_generator.pt` from [nvidia/bigvgan_v2_44khz_128band_512x](https://huggingface.co/nvidia/bigvgan_v2_44khz_128band_512x), NVIDIA, with its weight normalisation folded into the stored weights | MIT: `vae/LICENSE-BigVGAN` | | `mel_converter.` | The mel filter bank and window | MMAudio | CC BY-NC 4.0 | Every `vae.` tensor equals MMAudio's `v1-44.pth` with that folding applied, and every `vocoder.` tensor equals NVIDIA's generator with its own. Kandinsky Lab publishes the file inside its MIT repositories. MMAudio publishes its checkpoints under CC BY-NC 4.0, for non-commercial use only, and that licence is the one carried here. It is mirrored for non-commercial use, unchanged from Kandinsky Lab's file. ## Not mirrored here | File | Where it is | Why | |---|---|---| | `hunyuan_video_vae_bf16.safetensors`, the video VAE | [Comfy-Org/HunyuanVideo_repackaged](https://huggingface.co/Comfy-Org/HunyuanVideo_repackaged), `split_files/vae/` | Tencent Hunyuan Community License |