Text-to-Video
Safetensors
MLX
Wan2.2
mlx-gen
mflux
apple-silicon
8-bit precision
mixed-q8-bf16
wan
video-generation
image-to-video
Instructions to use AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-ti2v-5b-diffusers-8bit AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit
- Wan2.2
How to use AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Update TI2V-5B q8 package to current mixed q8/BF16 policy
Browse files- README.md +13 -9
- transformer/0.safetensors +2 -2
- transformer/1.safetensors +2 -2
- transformer/2.safetensors +2 -2
- transformer/model.safetensors.index.json +34 -46
- vae/0.safetensors +2 -2
- vae/model.safetensors.index.json +7 -7
README.md
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@@ -51,13 +51,14 @@ weights at BF16 runtime precision.
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Measured on 2026-06-04 with `mlx-gen 0.18.10` on an Apple M5 Max with 128 GiB unified memory.
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Validation profile: `1280x704`, 17 frames, 20 denoising steps, guidance `5`, 24 fps, seed `321`,
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explicit empty negative prompt.
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| Layout | Storage |
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| Upstream source snapshot | 31.9 GiB | 10.6 GiB | 102.7 GiB | 13.7 GiB | 58.5 GiB | 216.2 s | [base-source.mp4](validation/ti2v5b-clean/base-source.mp4) |
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| Prepared BF16 package | 21.2 GiB | 10.6 GiB | 102.6 GiB | 14.5 GiB | 58.5 GiB | 261.6 s | [prepared-bf16.mp4](validation/ti2v5b-clean/prepared-bf16.mp4) |
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| This mixed q8/BF16 package | 16.9 GiB | 6.3 GiB | 103.7 GiB | 13.8 GiB | 54.2 GiB | 243.4 s | [mixed-q8-bf16.mp4](validation/ti2v5b-clean/mixed-q8-bf16.mp4) |
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This package reduces storage, logical model bytes, active MLX model bytes, and MLX allocator peak in
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the validation profile. It did not reduce full-process physical peak memory in this profile because
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The source and prepared BF16 package produced byte-identical decoded MP4 frames. This mixed q8/BF16
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package stayed visually in the same family with mean frame MAE `1.66` versus source/BF16.
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`Storage` is the Hugging Face repository total. `
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VAE tensor footprint measured from MLX arrays
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`
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Validation assets:
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Measured on 2026-06-04 with `mlx-gen 0.18.10` on an Apple M5 Max with 128 GiB unified memory.
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Validation profile: `1280x704`, 17 frames, 20 denoising steps, guidance `5`, 24 fps, seed `321`,
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explicit empty negative prompt. This is a large normal-cache profile, not a `--low-ram` profile and
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not comparable to the A14B short low-RAM rows as a model-size memory statement.
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| Layout | Storage | Wan MLX Model | MLX Active After Generation | Full-Process Physical Peak | Max RSS | MLX Peak | Total Time | Output |
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| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | --- |
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| Upstream source snapshot | 31.9 GiB | 10.6 GiB | 10.3 GiB | 102.7 GiB | 13.7 GiB | 58.5 GiB | 216.2 s | [base-source.mp4](validation/ti2v5b-clean/base-source.mp4) |
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+
| Prepared BF16 package | 21.2 GiB | 10.6 GiB | 10.3 GiB | 102.6 GiB | 14.5 GiB | 58.5 GiB | 261.6 s | [prepared-bf16.mp4](validation/ti2v5b-clean/prepared-bf16.mp4) |
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+
| This mixed q8/BF16 package | 16.9 GiB | 6.3 GiB | 6.1 GiB | 103.7 GiB | 13.8 GiB | 54.2 GiB | 243.4 s | [mixed-q8-bf16.mp4](validation/ti2v5b-clean/mixed-q8-bf16.mp4) |
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This package reduces storage, logical model bytes, active MLX model bytes, and MLX allocator peak in
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the validation profile. It did not reduce full-process physical peak memory in this profile because
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The source and prepared BF16 package produced byte-identical decoded MP4 frames. This mixed q8/BF16
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package stayed visually in the same family with mean frame MAE `1.66` versus source/BF16.
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+
`Storage` is the Hugging Face repository total. `Wan MLX Model` is the loaded Wan transformer plus
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VAE tensor footprint measured from MLX arrays; it excludes the UMT5 text encoder and video/save
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buffers. `MLX Active After Generation` is the live MLX allocator footprint after `generate_video()`
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returns, before cleanup. `Full-Process Physical Peak` is Darwin `phys_footprint` sampled from model
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initialization through MP4 save and health validation. `Max RSS` can under-report Apple
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unified-memory/Metal pressure, and `MLX Peak` is only the MLX allocator high-water mark.
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Validation assets:
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{
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"metadata": {
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-
"quantization_level": "
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-
"mflux_version": "0.18.
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},
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"weight_map": {
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"encoder.conv_in.conv3d.weight": "0.safetensors",
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@@ -88,10 +88,6 @@
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"encoder.norm_out.weight": "0.safetensors",
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"encoder.conv_out.conv3d.weight": "0.safetensors",
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"encoder.conv_out.conv3d.bias": "0.safetensors",
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-
"quant_conv.conv3d.weight": "0.safetensors",
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-
"quant_conv.conv3d.bias": "0.safetensors",
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-
"post_quant_conv.conv3d.weight": "0.safetensors",
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-
"post_quant_conv.conv3d.bias": "0.safetensors",
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"decoder.conv_in.conv3d.weight": "0.safetensors",
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"decoder.conv_in.conv3d.bias": "0.safetensors",
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"decoder.mid_block.resnets.0.norm1.weight": "0.safetensors",
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@@ -199,6 +195,10 @@
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"decoder.up_blocks.3.resnets.2.conv2.conv3d.bias": "0.safetensors",
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"decoder.norm_out.weight": "0.safetensors",
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"decoder.conv_out.conv3d.weight": "0.safetensors",
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-
"decoder.conv_out.conv3d.bias": "0.safetensors"
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}
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}
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{
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"metadata": {
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+
"quantization_level": "None",
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+
"mflux_version": "0.18.9"
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},
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"weight_map": {
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"encoder.conv_in.conv3d.weight": "0.safetensors",
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| 88 |
"encoder.norm_out.weight": "0.safetensors",
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"encoder.conv_out.conv3d.weight": "0.safetensors",
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"encoder.conv_out.conv3d.bias": "0.safetensors",
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"decoder.conv_in.conv3d.weight": "0.safetensors",
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"decoder.conv_in.conv3d.bias": "0.safetensors",
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| 93 |
"decoder.mid_block.resnets.0.norm1.weight": "0.safetensors",
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| 195 |
"decoder.up_blocks.3.resnets.2.conv2.conv3d.bias": "0.safetensors",
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"decoder.norm_out.weight": "0.safetensors",
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| 197 |
"decoder.conv_out.conv3d.weight": "0.safetensors",
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+
"decoder.conv_out.conv3d.bias": "0.safetensors",
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+
"quant_conv.conv3d.weight": "0.safetensors",
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+
"quant_conv.conv3d.bias": "0.safetensors",
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+
"post_quant_conv.conv3d.weight": "0.safetensors",
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+
"post_quant_conv.conv3d.bias": "0.safetensors"
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}
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}
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