Editing
AI Image Upscaler on Martini
From draft to print-ready, on the canvas. Generate stills at the model default resolution, fan into the image-upscale tool only on the asset you ship, and chain the polished output into video, product placement, or print export — no separate tool, no re-upload, no transcode.
What this feature solves
AI image generation defaults to mid-range resolutions because that is the cost and latency sweet spot for iteration. The drafts are perfect for review, layout, and creative decisions, but the moment a brand asks for the chosen still in 4K for a billboard, in 8K for packaging, or at print DPI for a catalog page, the gap shows up. Regenerating at higher resolution is sometimes possible but expensive and slow; sending the draft to a separate upscaler is the more common path, and that path is full of hidden costs.
The hidden cost is the round-trip. Download the draft, upload it to an upscaler, wait for the queue, download the result, re-import to the canvas or the editor. Five steps, often with format and color-profile losses on each handoff. For a campaign with thirty placements, that round-trip lives in every single asset path. Multiply by the number of revisions a brand reviews and the production hours pile up — most of which is admin overhead, not creative work.
The deeper issue is upscale quality. Generic upscalers smooth or sharpen indiscriminately, and the result often looks plastic, especially on faces, fabric, and brand-controlled product detail. AI-aware upscalers preserve detail better, but only if the upscale lives in the same chain as the source generation so the tool sees the full context. Without that chain, the upscale is guesswork on a downloaded JPG.
Why Martini is different
On Martini, the image-upscale tool is a node on the same canvas as your generation. Wire the chosen still — generated on Nano Banana 2, Imagen 4, Flux, Midjourney, or any of the supported image models — into the upscale tool node, target the resolution, and run. The upscale reads the upstream image directly with no intermediate download. Lineage is preserved, so swapping the upstream still automatically refreshes the upscaled output. The chain becomes generate → review → choose → upscale, all inside the canvas.
Multi-model fanout pairs with selective upscale. Run a hero asset across Nano Banana 2, Flux, Imagen 4, and Midjourney in parallel, pick the winner, and upscale only the chosen take. You waste no upscale credits on rejected branches and the polished master comes from the same canvas where the creative decisions happened. For brands running large catalogs or multi-placement campaigns, this is the meaningful efficiency: ten thousand assets at draft, only the chosen masters at upscale resolution.
Export and chaining close the loop. Once upscaled, the still chains into product photography placements, video reference inputs, brand asset packs, or direct download for print and digital delivery. The upscale fits the same pattern as every other Martini node — connect, run, chain, export — and the brand asset library becomes a coherent canvas rather than a folder of disparate downloads.
Common use cases
Take a hero product still from draft to billboard delivery
Generate at draft, fan across image models, pick the winner, and upscale only the master to 4K or 8K for outdoor placement.
Prepare assets for print and packaging
Upscale the chosen still to print DPI before sending to the brand asset pack — no re-upload to a separate print prep tool.
Hero shot for a brand campaign across digital and OOH
One upscaled master serves the social, web, and out-of-home placements at the resolution each platform requires.
Sharpen a character reference before video generation
Upscale the canonical character portrait so the downstream Vidu or Kling video shots anchor to a higher-fidelity still.
Archival-quality output from a draft generation
For campaigns that demand archival deliverables, upscale the chosen final to a high-DPI master before NLE or asset-pack export.
Save the upscale step in the campaign canvas template
Once the chain works, every future hero asset moves through the same generate → fan-out → upscale sequence baked into the template.
Recommended model stack
midjourney
imageStylized hero stills that benefit from sharpening into print-grade resolution.
flux
imageHigh-fidelity creative output with detail that holds up through upscale.
nano-banana-2
imageReference-driven character and product stills suited to brand-grade upscale.
imagen-4
imagePhotoreal output with strong tonal range — pairs well with high-resolution upscale.
How the workflow works in Martini
- 1
1. Generate stills at the model default resolution
Run Nano Banana 2, Imagen 4, Flux, or Midjourney at the default. Iterate at draft resolution to keep cost low while you find the winning take.
- 2
2. Fan out across models for hero assets
Wire one reference into multiple image nodes with different models. Compare on the canvas and pick the strongest take.
- 3
3. Connect the chosen still to the image-upscale tool
Drop the image-upscale tool node and wire the chosen still into it. Set target resolution — print DPI, 4K, 8K, whatever the deliverable requires.
- 4
4. Run the upscale and review for artifacts
Compare upscaled output to the source. Look at faces, fabric, fine product detail — the places where upscale artifacts typically surface.
- 5
5. Chain into the next downstream node or export
Wire the upscaled still into a video reference node, a product placement node, or send directly to download for print delivery.
- 6
6. Save the chain as a campaign template
Once the generate → fan-out → upscale chain works, save the canvas. Future campaign hero assets move through the same template.
Example workflow
A consumer brand is launching a new fragrance and needs three hero stills: one for a billboard, one for a magazine print spread, one for a packaging mockup. The team builds a canvas with the brand color script and product reference wired into four image nodes — Nano Banana 2, Imagen 4, Flux, Midjourney — running the same prompt for each placement type. After two rounds of iteration at draft resolution, the team picks one winner per placement (Imagen 4 for the billboard, Flux for the print spread, Nano Banana 2 for the packaging). Each chosen still wires into an image-upscale tool node — billboard target 8K, print spread target 4K with print DPI, packaging at native print DPI. The upscaled masters chain to the brand asset pack and download. Three placements, three masters, one canvas, zero round-trips through external tools.
Tips and common mistakes
Tips
- Iterate at draft resolution, upscale only the takes you ship. Cheap iteration first, expensive upscale last.
- Watch face and fabric detail after upscale — those are the most upscale-sensitive areas in human or fashion subjects.
- For brand-controlled product detail, compare the upscale against the source pixel-by-pixel to ensure fidelity.
- Pair the upscale with a brand-color reference earlier in the chain so the upscaled output stays on palette.
- Save the canvas as a campaign template the moment the chain works. Reuse beats rebuild.
Common mistakes
- Running upscale on every candidate. The upscale step is post-decision; spend credits only on chosen masters.
- Expecting AI upscale to beat a real high-resolution shoot. Upscale rescues a draft; it does not replace a top-tier studio capture.
- Skipping the artifact review pass. Subtle hair, edge, and skin artifacts can sneak through and only show up in print or large-format display.
- Confusing the upscale tool with image generation. Upscale polishes; the source model creates — both nodes belong on the canvas.
- Downloading the upscaled file and re-uploading for the next step. Chain it on the canvas instead.
Related how-to guides
Related models and tools
Tool
AI Image Upscaling
Upscale images and keyframes before final video generation on Martini.
Tool
AI Background Removal
Remove backgrounds from images for assets and compositing on Martini.
Provider
Google's Veo video, Imagen image, and Nano Banana model workflows on Martini.
Provider
ByteDance
ByteDance's Seedance video and Seedream image model families on Martini.
Provider
OpenAI
OpenAI's GPT Image and Sora video model workflows available on Martini.
Related features
AI Video Upscaler — Polish AI Video to 4K on Martini
Improve AI video resolution and polish outputs on Martini's canvas.
AI Product Photography — Studio-Quality Product Images on Martini
Generate studio-quality product photos for e-commerce on Martini's canvas.
AI Photo Restoration — Restore Old Photos on Martini
Restore old, damaged, or low-quality photos with AI on Martini's canvas.
AI Background Remover — Cutout Subjects on Martini
Prepare product, character, and compositing assets with AI background removal on Martini.
AI Lip Sync — Sync Voice and Dialogue to Portraits and Video
Sync voiceovers, dialogue, and music to portraits and video on Martini using lip-sync models.
AI Camera Control — Orbit, Push, Pull, Pan, Crane
Direct AI video like a real DP — Sora 2, Kling 3, Runway Gen-4, Veo with director-level shot planning on Martini's canvas.
AI Video Editing — Transform and Extend Existing Clips
Restyle, replace, extend, and transform existing clips on Martini's canvas — Runway Aleph, Kling O3, Wan, Seedance 2 chained into a real edit.
Related docs
Related reading
Comparisons
Frequently asked questions
Does Martini generate images at 8K natively?
No. Martini generates at the model default resolution to keep iteration fast and cost-efficient, then runs the image-upscale tool only on the chosen master. The separation lets you iterate cheaply and spend upscale credits only on assets you ship.
Which AI image upscale tool does Martini use?
The image-upscale tool is a routed node — the underlying engine is determined by workspace defaults. The recommendedModels above are the source image models whose drafts upscale well; the upscale step is the tool, not a separate model choice.
Can AI upscale replace a real high-resolution photo shoot?
For top-tier brand and editorial work, no — a real shoot still wins for shadow detail, skin texture, and material rendering. Upscale is most valuable as a rescue when the source draft is what you have and the campaign demands higher-resolution delivery.
Will upscale preserve brand color accuracy?
Generally yes for routine ranges, but every upscale step can shift tonal values slightly. For brand-critical placements, review the upscaled output against the brand color reference before locking, and run the chain through a color-managed export when possible.
How is this different from a generic upscaler website?
A generic upscaler is a separate tab — download, upload, download. Martini puts the upscale on the same canvas as the generation, with lineage and chained downstream nodes. Iteration loops stay tight and the master comes from the same canvas where the creative work happened.
How much does an image upscale cost?
Each upscale deducts credits proportional to the input resolution and target resolution. Upscale only the masters you ship; let candidates stay at draft to keep cost efficient.
Build it on the canvas
Open Martini and wire this workflow up in minutes. Free to start — no card required.