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QuantStack/Wan2.2-I2V-A14B-GGUF

QuantStack·Image-to-video·active

SyncDev model directory · Profile updated Oct 7, 2026

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QuantStack/Wan2.2-I2V-A14B-GGUF is a source-linked Hugging Face repository assigned to Image-to-video. Its recorded task interface accepts image and produces video.

Key specifications

Specification score
10.0

The specification score summarizes recorded features and limits. It is not a benchmark result.

Inputs and outputs

Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.

Accepts

  • Image input

Produces

  • Video output

Capabilities

VisionStreaming

What is QuantStack/Wan2.2-I2V-A14B-GGUF?

QuantStack/Wan2.2-I2V-A14B-GGUF: overview

QuantStack/Wan2.2-I2V-A14B-GGUF is a Hugging Face repository returned by the public Image-to-video task feed. Its recorded download count is 342,292 and it has 383 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.

Task fit

This record is categorized for Image-to-video. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.

Source record

The public repository lists gguf as its library metadata. Its recorded tags include gguf, image-to-video, en, zh, base_model:Wan-AI/Wan2.2-I2V-A14B, base_model:quantized:Wan-AI/Wan2.2-I2V-A14B, license:apache-2.0, region:us. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.

Check reference fidelity through the clip

Use source images with distinct faces, objects and fine details. Inspect motion, identity preservation and temporal artifacts across every frame, then compare generation time and failure rates.

Recorded interface

The Hugging Face task assignment records image as input and video as output for QuantStack/Wan2.2-I2V-A14B-GGUF. This interface summary comes from the repository’s recorded Image-to-video task classification. It helps readers distinguish a text, image, audio, video, document, embedding, or prediction workflow without inferring undocumented API behavior. Model wrappers can expose different preprocessing and response formats, so verify the upstream model card and the exact runtime before deployment.

Related models

Explore QuantStack models and the image-to-video collection. Use the comparison tool to inspect a second candidate.

How to evaluate QuantStack/Wan2.2-I2V-A14B-GGUF

Compare the model on the work you need to complete.

Tasks and inputs

QuantStack/Wan2.2-I2V-A14B-GGUF is listed for Image-to-video. It accepts image and produces video. Use the publisher’s input format and preprocessing for your chosen deployment.

Capacity and cost

Choose duration, resolution and frame rate together. Compare the cost of an accepted clip, including repeat generations.

Choosing a deployment

Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.

Frequently asked questions

QuantStack/Wan2.2-I2V-A14B-GGUF is a Hugging Face repository listed for the Image-to-video task. Open the linked model card to verify the checkpoint, deployment requirements and current source details.

More profiles in Image-to-video

These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.

bullerwins

bullerwins/Wan2.2-I2V-A14B-GGUF

bullerwins/Wan2.2-I2V-A14B-GGUF is a source-linked Hugging Face repository assigned to Image-to-video. Its recorded task interface accepts image and produces video.

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