AI image upscale on Martini takes a generated still — a Midjourney render, Flux character, Nano Banana 2 product shot, or any uploaded reference — and outputs a higher-resolution version with sharper edges and recovered detail. Use it before image-to-video so keyframes survive the motion model, or as a final pass when you need print-ready or 4K product hero stills.
Image upscale takes a single still image and reconstructs it at a higher target resolution by hallucinating plausible detail in faces, hair, fabric, text, and product surfaces. Inputs are typically 1024px or 2048px AI generations; outputs land at 4K or higher depending on the scale factor you choose. The model is tuned to preserve the source composition, color, and identity while rebuilding texture instead of simply interpolating pixels.
On the Martini canvas, image upscale is a tool node downstream of any image generation or upload. Connect the source image, choose a scale factor, and the upscaled file writes back to a new node. From there it can flow into a video model as a high-fidelity keyframe, into an export node for delivery, or back into another image edit chain.
Generate or upload your source image first. Stronger upscales come from cleaner source images, so spend prompt iterations getting the composition right at the model's native resolution before reaching for the upscaler. Midjourney, Flux, and Nano Banana 2 are common upstream sources.
Drop an Image Upscale tool node onto the canvas and wire the source image into its input. Pick a scale factor — 2x is the default for most production work, 4x for hero shots that will fill a screen or print page. Higher factors cost more credits and take longer.
Submit the job. Once the upscaled image returns, inspect critical regions — faces, text, logos, fine fabric — at 100% zoom. If detail looks invented or hallucinated incorrectly, lower the scale factor or regenerate the source at a higher base resolution before retrying.
Chain the upscaled image into your downstream workflow. For video, feed it into Seedance 2 or Kling 3 as a high-resolution starting frame; for ecommerce, flow it into background removal or a final compositing node; for storyboards, drop it into the export bundle for review.
Batch upscale by duplicating the upscale node per source image. The canvas is good at parallel runs — you can queue a dozen frames and let them complete while you work on other parts of the project.
Pair with Midjourney to upscale stylised renders for hero stills and storyboards.
View modelSharpen Flux character renders before image-to-video so faces survive the motion model.
View modelLift Nano Banana 2 product shots to 4K for ecommerce listings and ad creative.
View modelIf your image model maxes out at 1024 or 2048, upscale is the only path to 4K. If the model supports a native higher resolution (some Flux and Imagen variants do), prefer the native render for cleaner detail.
A good upscaler preserves the identity in the source. If you're chaining several upscales or running aggressive 4x passes, identity can drift slightly — keep the original around as a reference.
Upscale last. Edits like background removal, color shifts, or compositing should happen at the source resolution; upscale once you've locked the look so the model has the cleanest possible input.
Indirectly. Upscale your starting frame before image-to-video so the motion model has more detail to work from; then run video upscale on the resulting clip if you need 4K delivery.
Most upscalers cap at 4x in a single pass. Stacking passes beyond that usually introduces artefacts. For oversized print, regenerate at the highest native resolution and upscale once.
Chain AI Image Upscaling with other AI models on Martini's infinite canvas. No GPU required — start free.
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