Workflows/Animate images locally with Wan2.1

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Animate images locally with Wan2.1

Turn still images into silent video clips with the Wan2.1 480p image-to-video model, a ready-to-load ComfyUI workflow and practical memory settings.

Verified sourceSource checked 9/29/2026

LOCALRENTED GPU

Freshness 10 out of 100. Repository age: 597 days old, Feb 25, 2025. Measures age, not quality.

Popularity 68 out of 100. 129,090 downloads in 30 days; 240 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source

Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

Before you begin

Hardware

Estimated full-pipeline starting points: 14B I2V FP16, full-precision text encoder, VAE, vision encoder, batch 1, 832 × 480, 33 frames, 16 fps. CPU offload uses system RAM.

Machine	Wan2.1 I2V 14B · FP16
NVIDIA GPU · 16 GB + 64 GB RAM	Runs with heavy CPU offload; keep 33 frames and expect slower processing. Estimated.
NVIDIA GPU · 32 GB + 64 GB RAM	Good starting capacity with CPU offload; full 14B pipeline is larger than VRAM. Estimated.
AMD GPU · 24 GB + 64 GB RAM	Use a supported ROCm card; CPU offload and 33 frames. Estimated, not a speed result.
Intel Arc GPU · 16 GB + 64 GB RAM	XPU backend required; heavy offload at 33 frames. Estimated; expect waiting.
Apple Silicon · 64 GB unified	Tight starting capacity at 33 frames; close other apps. Full-precision weights. Estimated.
Apple Silicon · 96 GB unified	More room for full weights, VAE and short-clip workload. Metal route. Estimated.
CPU only · 96 GB RAM	Not recommended for this video workflow; use a supported GPU or rent a 48 GB GPU.

Memory capacity is not a speed measurement. AMD/Intel require the correct supported GPU backend; Mac uses Apple Silicon Metal. These are source-informed estimates, not YouRunAI hardware benchmarks. Multi-GPU memory is not pooled by this graph.

LOCAL IMAGE ANIMATIONSOURCE-LINKED SETUP

Animate images locally with Wan2.1

Turn still images into silent video clips with the Wan2.1 480p image-to-video model, a ready-to-load ComfyUI workflow and practical memory settings. Choose your package and machine, then use Comfy Desktop to choose a built-in template or the supplied workflow JSON, download its models and save a result.

Choose a package Load the visual workflow Check the result

BEFORE YOU BEGIN

The documented package

This setup uses the package documented for this task. Review its source and supported platforms before starting.

Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.

CURRENT SETUP

Wan2.1 I2V 14B · FP16 · official

Estimated for 832 × 480, 33 frames, batch 1. Use 64 GB system RAM for CPU offload; 96 GB leaves more room. The 32.8 GB diffusion file alone exceeds a 32 GB card. Close other GPU apps. Higher resolution, more frames and a second generation increase memory.

Freshness 10 out of 100. Repository age: 597 days old, Feb 25, 2025. Measures age, not quality.

Popularity 88 out of 100. 4,036,182 downloads in 30 days; 1,009 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

Check the date source

Popularity · adoption

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

View weight source

THE WORKFLOW

Set up Wan2.1 I2V 14B · FP16 on your machine

Choose your computer first, then its GPU path. Follow the visual setup and import the linked workflow.

CHOOSE YOUR SETUPWindows

Hardware type

NVIDIA (CUDA) through Comfy Desktop. An existing working ComfyUI installation can use the same JSON and model files; a second installation is unnecessary.

Open Comfy Desktop — install only if needed

Already have a working, current ComfyUI? Skip installation and continue to the workflow choice below. Otherwise: Download the Windows installer, open the .exe and follow the setup screens. Launch Comfy Desktop from the Start menu. Choose New Instance → Standalone, the Stable channel and NVIDIA (CUDA) when the hardware options appear. Let the app install Python and dependencies for you; no separate Git or Python setup is needed. Use the current NVIDIA driver. For RTX 20-series and newer, including RTX 5090, select the recommended stable CUDA build; respect any driver or GPU-compatibility warning. When ready, click the instance card to open ComfyUI. In the card’s ⋮ → Manage → About, confirm the expected GPU and PyTorch backend rather than CPU before downloading large files.

Download Comfy Desktop Official Windows installation NVIDIA driver downloads

Choose Templates or the supplied workflow JSON

For the fewest setup changes, download this package’s JSON below (use Save link as if it opens as text), then drag it onto the ComfyUI canvas. It already contains the exact model selections, preset and output path used in this guide; no custom-node packs are needed. Or use ComfyUI Templates: click Templates in the sidebar (also Workflow → Browse Workflow Templates), search for “Wan 2.1 Image to Video” and open that exact template. It uses the matching 14B 480p image-to-video model. Its default text encoder is FP8: to match this package, select umt5_xxl_fp16.safetensors in Load CLIP from the downloads below. Apply the 832 × 480, 33-frame, 16-fps preset and fixed seed below; set SaveVideo format to mp4 and codec to h264 instead of auto. Set SaveVideo filename_prefix to YouRunAI/wan-animate so the save-location instructions match. If the exact template is absent, use the JSON or update ComfyUI and its template package. Use one route per run. The supplied JSON remains available if you prefer the expanded graph or want this guide’s exact setup.

Download this exact ComfyUI workflow JSON How to open ComfyUI Templates Official Wan 2.1 Image to Video template Original official graph and explanation

Download the matching model files

If you chose Templates, skip its FP8 text-encoder suggestion; use the FP16 encoder listed here. In Desktop’s missing-model dialog, click Download for each required file and wait for completion. Models already present can be reused. If the prompt is unavailable, use the exact links below: open ☰ → Desktop Settings → Storage → Shared Models, then click the folder icon beside Primary. The tree starts INSIDE that primary model folder; do not add another models folder. Older manual/portable installations use their existing ComfyUI/models folder instead. Confirm Load Diffusion Model selects wan2.1_i2v_480p_14B_fp16.safetensors, Load CLIP selects umt5_xxl_fp16.safetensors with type wan, and Load VAE selects wan_2.1_vae.safetensors. Load CLIP Vision must select clip_vision_h.safetensors. After downloads finish, reload the workflow and reselect a file if a loader still shows it missing.

Put these files in Your primary model folder/4 required files

diffusion_models/

wan2.1_i2v_480p_14B_fp16.safetensorsImage-to-video checkpoint; not interchangeable with T2VGet file

text_encoders/

umt5_xxl_fp16.safetensorsFull-precision text encoder; avoids FP8-only backend assumptionsGet file

vae/

wan_2.1_vae.safetensorsDecodes the generated video framesGet file

clip_vision/

clip_vision_h.safetensorsEncodes the uploaded starting imageGet file

Desktop model downloads Find your shared model folder

Upload your image and set the motion

In Load Image, upload one landscape product or scene photo that you own. Crop it to a 26:15 ratio first to match 832 × 480, using your normal image editor. The graph passes this image through both CLIP Vision Encode and WanImageToVideo; do not bypass Load Image. For the first run, describe a small camera move rather than a major scene change. Enter this in the positive CLIP Text Encode node: The camera moves slowly toward the subject. Gentle natural motion, preserve the subject, stable background, smooth continuous shot. Set WanImageToVideo to width 832, height 480, length 33 and batch_size 1. Set KSampler to 20 steps, CFG 6, uni_pc sampler, simple scheduler, denoise 1. Keep ModelSamplingSD3 shift at 8. Set seed to 20260928 and control_after_generate to fixed. CreateVideo must be 16 fps; SaveVideo is MP4/H.264. The result is 33 frames ÷ 16 fps ≈ 2.06 seconds, silent. Do not add interpolation or an upscaler for the first run.

Run and inspect the playable clip

Click Run once. Wait for the active queue item to finish; the queue shows progress. The first run can take longer while models load. Open the SaveVideo preview and play it. Verify motion, 832 × 480 dimensions, approximately 2.06 seconds at 16 fps and no audio. A completed render is the success check; importing a graph alone is not.

Save your result and return later

Use the SaveVideo preview menu to download your MP4. ComfyUI also saves it in the configured output folder’s YouRunAI subfolder. Find that folder in Desktop Settings → Storage → Shared Output; if shared output is disabled, use the instance’s Manage → Storage → Output Directory. Save/export the workflow JSON after editing settings so you can reopen the same setup. Change one prompt or seed and click Run for another result. To stop an unwanted render, use the queue’s Cancel/Interrupt control. To shut down, return to the instance card → ⋮ → Stop; tomorrow, open Comfy Desktop, click that card and load your saved JSON. No terminal launch commands are needed.

SUCCESS CHECK · Wan2.1 I2V 14B · FP16

Your clip is playable and saved

The SaveVideo preview plays a silent 832 × 480 MP4 of about 2.06 seconds. Its file is in your configured output folder’s YouRunAI subfolder. You can reopen the saved workflow, keep the same files and change one prompt or seed to make another clip.

Verified refers to the linked model/runtime documentation and reviewed graph structure. Hardware advice is Estimated. No render-time or YouRunAI physical-execution claim is made. This focused setup uses publisher model packages; it does not bundle a speculative uncensored LoRA or claim that every third-party derivative works.

Back to setup steps

When it doesn’t go to plan

A loader says the model file is missing

Check the exact filename in this package’s file tree and finish the Desktop download. If downloading manually, put the file inside the Primary shared model folder’s indicated subfolder; for manual/portable ComfyUI use its models folder. Reload the workflow and reselect the file. If it remains missing, stop the instance from its card menu and click the card to relaunch. A .safetensors file must not be a partial download or an HTML error page.

The GPU check fails or generation falls back to the CPU

Open the instance card → ⋮ → Manage → About and inspect Hardware and PyTorch. Confirm NVIDIA/CUDA, AMD/ROCm, Intel/XPU or Apple/MPS for your route. Update the vendor driver if needed. Desktop can change the PyTorch stack from its Manage panel (About → Change PyTorch; some versions place the picker on Update). Use an offered stable stack compatible with your actual GPU and OS. On Linux AMD, resolve any missing /dev/kfd or GPU-access warning using the vendor instructions. More VRAM does not fix an unsupported backend.

A core node is missing when the JSON is loaded

Update the active ComfyUI instance through its card → Manage → Update → Check for update, using Stable, then stop and reopen it and reload the JSON. Updating only the Desktop launcher does not update an older instance. The supplied graphs use ComfyUI core nodes; do not install unrelated custom-node packs to replace them. If a node is still absent in the current stable release, compare the linked official template requirements before changing release channels.

Generation runs out of memory

Cancel the current job and close other GPU applications. Keep batch_size 1. Reduce length from 33 to 17 frames (about 1.06 seconds at 16 fps); use 4n+1 frame counts. Keep width and height divisible by 16. The 14B weights require system-RAM offload; reducing frames does not make the weights smaller. Ensure at least 64 GB system RAM. If automatic offload is insufficient, add --lowvram in the instance’s Manage → Startup Args, then stop and reopen it. On Mac, reduce workload and close apps rather than disabling the system memory safety limit.

The clip duration or motion looks wrong

Confirm CreateVideo is 16 fps and the latent length is 33; changing FPS changes playback duration, not generated motion. Keep the fixed seed and try a simpler positive motion prompt. For image-to-video, confirm the uploaded image reaches both the vision encoder and WanImageToVideo. A T2V checkpoint cannot replace the I2V checkpoint.

REFERENCE LIBRARY

Sources and files

Original instructions, model files, and compatibility notes behind this setup.

11 SOURCES

01Official Wan ComfyUI examplescomfyanonymous.github.io 02Wan model publishergithub.com 03Official ComfyUI graph sourcegithub.com 04AMD GPU / OS compatibilityrocm.docs.amd.com 05Intel XPU setupdocs.pytorch.org 06Apple Metal setupdeveloper.apple.com 07Comfy Desktop installationdocs.comfy.org 08Comfy Desktop: manage GPU, updates and storagedocs.comfy.org 09Shared models and output foldersdocs.comfy.org 10Automatic model downloads from workflowsdocs.comfy.org 11Official built-in Wan 2.1 Image to Video templategithub.com

The model behind this workflow

Wan2.1 Image-to-Video · 14B

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Verified source