Top 10 Best AI Upscaling Video Software of 2026

Topaz Video AI is an AI upscaling video workflow built around frame interpolation and enhancement models that aim to increase perceived sharpness and reduce temporal artifacts during playback and editing. It supports converting between frame rates using interpolation, plus denoise and deblur passes that operate at the frame level rather than requiring manual per-clip tuning. It fits pipelines where rendered output is acceptable to generate offline and then reused in an editing timeline.

A key tradeoff is that higher quality settings and heavier upscaling or interpolation increases render time and can add processing artifacts on difficult sources like noisy footage with strong compression blocks. It is most useful when low-resolution or low-FPS inputs must be preserved as a higher-quality asset for later editing, archiving, or delivery, not when instant preview is required.

DVDFab Video Enhance AI is an AI upscaling and enhancement workflow aimed at generating higher-resolution video outputs from lower-resolution sources. The software applies AI-based restoration and sharpening passes to address block noise and soften edge artifacts that often appear after scaling or compression. It supports processing tailored to different source conditions, which helps when mixing recordings with varied resolutions and codec artifacts.

The main tradeoff is that aggressive enhancement can introduce oversharpening halos or texture changes on some content, which can require testing multiple settings per source type. This tool is best used when a batch of media needs consistent quality improvements, such as rebuilding a library of older downloaded files into a unified higher-resolution format, rather than making precise manual corrections on individual frames.

AVCLabs Video Enhancer AI focuses on AI upscaling with noise reduction and sharpening for improving perceived clarity in existing video files. The workflow supports exporting enhanced results per clip, with batch processing options that help when multiple segments need the same upscale treatment.

Enhancement modes are tuned for common quality problems such as low resolution, compression artifacts, and soft edges. The tool is aimed at practical output improvements rather than editing timelines or style-based transformations.

VideoProc Converter AI differentiates itself with AI-driven video processing tools bundled into one editor that focuses on upscaling and enhancement. The app provides AI upscaling with selectable scaling targets and supports batch conversion for processing multiple files.

It also includes noise reduction and frame interpolation options that can improve perceived clarity when source footage looks soft or low frame rate. The workflow centers on picking an input, choosing the enhancement pipeline, and exporting to common formats optimized for playback.

Remini Video Upscaler focuses on AI enhancement for existing video footage with an emphasis on face and detail restoration. The workflow typically uploads a video, selects an upscaling option, and generates a higher-resolution output with reduced blur.

Quality gains are most visible on low-resolution or soft sources, while fast motion can still show stabilization and artifact tradeoffs. It is best suited to quick, tool-driven restoration rather than deep manual control over enhancement parameters.

Runway specializes in AI video generation and editing workflows, and it also supports AI upscaling to increase video resolution. It is used for transforming clips into higher-detail versions while keeping a coherent look across time.

The tool’s value comes from integrating upscaling with broader creative controls for video, not just a standalone resize function. Effects can be iterated quickly inside an editing-oriented interface.

Azure Video Indexer primarily distinguishes itself with deep video understanding powered by Microsoft AI, including speech-to-text, face and object insights, and structured indexing for searchable playback. It is strong for workflow automation around existing video assets rather than delivering direct real-time AI upscaling inside the same pipeline.

Upscaling use cases typically require exporting or integrating outputs with separate image or video enhancement steps, which reduces end-to-end simplicity for pure upscaling projects. For teams that need both AI understanding and improved viewing experiences, it can anchor the metadata and retrieval layer while upscaling happens elsewhere.

Google Cloud Video Intelligence focuses on extracting labels, speech, and other metadata from video using managed machine learning services. It supports asynchronous video analysis workflows and can detect concepts, shot changes, OCR text in frames, and spoken words with timestamps.

This is not a native AI upscaling tool, but it can improve upscale outcomes by identifying content types, faces, text, and segments that deserve higher fidelity. Its strongest fit is pairing visual understanding with an external upscaler pipeline rather than replacing super-resolution itself.

Kapwing distinguishes itself with a browser-based editor that combines AI image tools with AI-powered video processing in one workflow. Upscaling is handled as part of its video editing pipeline, letting users increase resolution before export. The platform also supports trimming, cropping, and basic effects so upscaling fits into practical post-production tasks.

Clipchamp stands out for making AI upscaling part of an edit-and-export workflow inside a browser-based video editor. The platform supports automated video enhancement and common export pipelines so upscaled results fit standard social and playback targets.

Its approach prioritizes quick media turnaround over deep, parameter-level control typical of dedicated upscaling tools. Editing, trim, and asset management remain accessible while upscaling is applied near the end of the workflow.