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// Wan · Video generation

Wan-Dancer-14B: VRAM & local deployment

14B parameters. About 9.8 GB at 4-bit and 31.3 GB at BF16.

released 2026-07-10licence: Commercial OKmemory figures are estimates

01Specs

PublisherAlibaba Wan · Wan-AI
Family / seriesWan · Wan-Dancer
TypeVideo generation (image-to-video)
Parameters14B Source: official model name
LicenceApache-2.0 · Commercial OKPermissive licence (Apache-2.0 / MIT / CC-BY / OpenMDW): commercial use allowed.
Released2026-07-10 (Hugging Face repo created)

02How much VRAM it needs (estimate)

Video models: memory grows with resolution and clip length; official repos usually list a tested GPU in the card. Weights below are the main model only.

PrecisionWeightsWeights + overheadSmallest GPUMac
BF16 / FP16 (original)28.0 GB 31.3 GB 2 × RTX 5090 (64GB)Mac 64GB
FP8 / INT8 / Q8_014.9 GB 16.9 GB RTX 4090 24GBMac 36GB
4-bit (Q4_K_M / AWQ / GPTQ-Int4)8.5 GB 9.8 GB 12GB GPUMac 24GB

Bits per weight: BF16 16, FP8 8.5, 4-bit 4.85. “Fits” = total ≤ 90% of memory; Mac GPU can use ~2/3 of unified memory (≤36GB) or ~3/4 (larger). For MoE, all experts must be in memory, so size by total parameters. Method →

03How to run it

Only runtimes the publisher or the runtime’s official library names for this model.

Which inference engine to choose →

04Official repositories & quantised builds

1 official repo(s) from Wan-AI.

05Other Wan models

All 15 →
ModelParams4-bit totalReleased
Wan2.2-Animate-2-14B-Diffusers16.4B11.4 GB2026-08-06
Wan2.2-Animate-2-14B-Distilled-Diffusers16.4B11.4 GB2026-08-06
Wan2.2-Animate-14B-Diffusers17.3B12.0 GB2025-11-12
Wan2.2-S2V-14B16.3B11.4 GB2025-08-25
Wan2.2-I2V-A14B-Diffusers14.3B / 14B10.0 GB2025-07-28
Wan2.2-T2V-A14B-Diffusers14.3B / 14B10.0 GB2025-07-28
Wan2.2-TI2V-5B-Diffusers5B3.8 GB2025-07-28
Wan2.1-VACE-1.3B2.15B1.9 GB2025-05-13

06Sources

Data checked 2026-07-17. Parameters, context and licence are copied from the official repository; memory figures are our estimates.

Data updated: Self-host open models(UTC+8)