Text-to-Video
Safetensors
MLX
Wan2.2
mlx-gen
mflux
apple-silicon
bf16
wan
video-generation
image-to-video
Instructions to use AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16 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-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-ti2v-5b-diffusers-bf16 AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16
- Wan2.2
How to use AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16 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
Add TI2V-5B validation assets
Browse files
validation/ti2v5b-clean/metrics.json
ADDED
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| 1 |
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{
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| 2 |
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"validation_date": "2026-06-04",
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"machine": "Apple M5 Max, 128 GiB unified memory",
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"profile": {
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"prompt": "A short cinematic video of a glowing orange glass sphere floating above calm teal water, soft reflections, gentle camera movement",
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"negative_prompt": "",
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"width": 1280,
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"height": 704,
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"frames": 17,
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"steps": 20,
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"guidance": 5,
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"fps": 24,
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"seed": 321
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},
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"layouts": {
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"base_source": {
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"repo": "Wan-AI/Wan2.2-TI2V-5B-Diffusers",
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"storage_gib": 31.85,
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| 19 |
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"mp4": "base-source.mp4",
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| 20 |
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"total_seconds": 216.15181183815002,
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| 21 |
+
"generation_seconds": 215.164,
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| 22 |
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"physical_peak_gib": 102.67981120198965,
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| 23 |
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"rss_peak_gib": 13.703689575195312,
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| 24 |
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"resident_peak_gib": 13.702316284179688,
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| 25 |
+
"mlx_peak_gib": 58.507674764841795,
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| 26 |
+
"mlx_active_after_generate_gib": 10.348156608641148,
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| 27 |
+
"mlx_cache_after_generate_gib": 0.48403943702578545,
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| 28 |
+
"logical_model_gib": 10.62639182060957,
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| 29 |
+
"logical_transformer_gib": 9.313806891441345,
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| 30 |
+
"logical_vae_gib": 1.3125849291682243,
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| 31 |
+
"model_bits": null,
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| 32 |
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"health": {
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| 33 |
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"source": "validation_outputs/ti2v_memory_profile_2026_06_04/base_source.mp4",
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| 34 |
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"frame_count": 17,
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| 35 |
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"width": 1280,
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| 36 |
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"height": 704,
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| 37 |
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"fps": 24.0,
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| 38 |
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"luma_min": 7.228399753570557,
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| 39 |
+
"luma_max": 246.07899475097656,
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| 40 |
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"luma_mean": 174.08145500631895,
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| 41 |
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"mean_temporal_delta": 0.7045322582125664
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| 42 |
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}
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| 43 |
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},
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| 44 |
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"prepared_bf16": {
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| 45 |
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"repo": "AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16",
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| 46 |
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"storage_gib": 21.22,
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| 47 |
+
"mp4": "prepared-bf16.mp4",
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| 48 |
+
"total_seconds": 261.56354999542236,
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| 49 |
+
"generation_seconds": 260.648,
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| 50 |
+
"physical_peak_gib": 102.583978459239,
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| 51 |
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"rss_peak_gib": 14.515884399414062,
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| 52 |
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"resident_peak_gib": 14.515884399414062,
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| 53 |
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"mlx_peak_gib": 58.472518514841795,
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| 54 |
+
"mlx_active_after_generate_gib": 10.348156608641148,
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| 55 |
+
"mlx_cache_after_generate_gib": 0.48403943702578545,
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| 56 |
+
"logical_model_gib": 10.62639182060957,
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| 57 |
+
"logical_transformer_gib": 9.313806891441345,
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| 58 |
+
"logical_vae_gib": 1.3125849291682243,
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| 59 |
+
"model_bits": null,
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| 60 |
+
"health": {
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| 61 |
+
"source": "validation_outputs/ti2v_memory_profile_2026_06_04/prepared_bf16.mp4",
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| 62 |
+
"frame_count": 17,
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| 63 |
+
"width": 1280,
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| 64 |
+
"height": 704,
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| 65 |
+
"fps": 24.0,
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| 66 |
+
"luma_min": 7.228399753570557,
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| 67 |
+
"luma_max": 246.07899475097656,
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| 68 |
+
"luma_mean": 174.08145500631895,
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| 69 |
+
"mean_temporal_delta": 0.7045322582125664
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| 70 |
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}
|
| 71 |
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},
|
| 72 |
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"mixed_q8_bf16": {
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| 73 |
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"repo": "AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit",
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| 74 |
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"storage_gib": 16.86,
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| 75 |
+
"mp4": "mixed-q8-bf16.mp4",
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| 76 |
+
"total_seconds": 243.38612413406372,
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| 77 |
+
"generation_seconds": 242.664,
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| 78 |
+
"physical_peak_gib": 103.74846588075161,
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| 79 |
+
"rss_peak_gib": 13.800796508789062,
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| 80 |
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"resident_peak_gib": 13.79901123046875,
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| 81 |
+
"mlx_peak_gib": 54.187850546091795,
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| 82 |
+
"mlx_active_after_generate_gib": 6.063488639891148,
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| 83 |
+
"mlx_cache_after_generate_gib": 0.48403943702578545,
|
| 84 |
+
"logical_model_gib": 6.3417238518595695,
|
| 85 |
+
"logical_transformer_gib": 5.029138922691345,
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| 86 |
+
"logical_vae_gib": 1.3125849291682243,
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| 87 |
+
"model_bits": 8,
|
| 88 |
+
"health": {
|
| 89 |
+
"source": "validation_outputs/ti2v_memory_profile_2026_06_04/mixed_q8_bf16.mp4",
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| 90 |
+
"frame_count": 17,
|
| 91 |
+
"width": 1280,
|
| 92 |
+
"height": 704,
|
| 93 |
+
"fps": 24.0,
|
| 94 |
+
"luma_min": 7.866199493408203,
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| 95 |
+
"luma_max": 246.94140625,
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| 96 |
+
"luma_mean": 174.77739491182214,
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| 97 |
+
"mean_temporal_delta": 0.6711972616612911
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| 98 |
+
}
|
| 99 |
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}
|
| 100 |
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},
|
| 101 |
+
"comparisons": {
|
| 102 |
+
"base_vs_prepared_bf16": {
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| 103 |
+
"frame_count": 17,
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| 104 |
+
"byte_identical_decoded_frames": true,
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| 105 |
+
"mean_frame_mae": 0.0,
|
| 106 |
+
"max_frame_mae": 0.0,
|
| 107 |
+
"max_abs_channel_delta": 0
|
| 108 |
+
},
|
| 109 |
+
"base_vs_mixed_q8_bf16": {
|
| 110 |
+
"frame_count": 17,
|
| 111 |
+
"byte_identical_decoded_frames": false,
|
| 112 |
+
"mean_frame_mae": 1.6606264709363858,
|
| 113 |
+
"max_frame_mae": 1.7536328864820077,
|
| 114 |
+
"max_abs_channel_delta": 133
|
| 115 |
+
},
|
| 116 |
+
"prepared_bf16_vs_mixed_q8_bf16": {
|
| 117 |
+
"frame_count": 17,
|
| 118 |
+
"byte_identical_decoded_frames": false,
|
| 119 |
+
"mean_frame_mae": 1.6606264709363858,
|
| 120 |
+
"max_frame_mae": 1.7536328864820077,
|
| 121 |
+
"max_abs_channel_delta": 133
|
| 122 |
+
}
|
| 123 |
+
},
|
| 124 |
+
"interpretation": {
|
| 125 |
+
"prepared_bf16": "Storage/download reduction only for this profile; MLX-Gen already casts upstream Wan transformer and VAE weights to BF16 at runtime.",
|
| 126 |
+
"mixed_q8_bf16": "Reduces storage, logical model bytes, active MLX bytes, and MLX allocator peak. This profile did not reduce full-process Darwin physical peak because non-model transient memory dominated the run."
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| 127 |
+
}
|
| 128 |
+
}
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