Generate Image
Create AI-generated images from text prompts using 23 provider models with configurable style, aspect ratio, resolution, and quality.
Overview
Generate Image is the primary text-to-image node. It accepts a text prompt (with optional style presets, negative prompts, and reference images) and produces an image via one of 23 AI providers. The default provider is Nano Banana Pro at 16:9 aspect ratio.
Configuration
| Field | Type | Default | Description |
|---|---|---|---|
| Provider | select | nano-banana-pro |
AI model to use for generation (24 options) |
| Prompt | text | "" |
Text description of the image to generate |
| Style | select | "" |
One of 16 presets (Photorealistic, Cinematic, Anime, Digital Art, Oil Painting, Watercolor, Children’s Book, Comic Book, Pixel Art, 3D Render, Pencil Sketch, Pop Art, Minimalist, Retro/Vintage, Fantasy, Noir) or “Custom…” free text. Style text is appended to the prompt at execution time. |
| Negative Prompt | text | "" |
Elements to exclude. Sent natively for imagen4, ideogram, qwen; appended as “Avoid:…” for other providers. |
| Aspect Ratio | select | "16:9" |
Provider-specific ratio sets (see table below) |
| Resolution | select | varies | Available for nano-banana-pro, nano-banana-2, flux, flux-flex only: 1K, 2K, 4K |
| Quality | select | varies | Available for gpt-image (medium/high), seedream/seedream-5-lite (basic 2K / high 4K), and seedream-5-pro (basic 1K / high 2K) |
| Rendering Speed | select | – | Available for ideogram-v3: turbo, balanced, quality |
| Seed | number | – | Reproducibility seed (supported by select providers) |
| Style Type | select | – | Ideogram-specific style parameter |
| Expand Prompt | boolean | – | Ideogram-specific prompt expansion toggle |
| Reference Images | image list | – | Supported by nano-banana, nano-banana-pro, nano-banana-2, nano-banana-2-lite only. Upload or select from library. |
| Character/Asset References | references | – | Connect Character, Object, or Location nodes for visual consistency |
| Strength | slider | varies | i2i denoising strength. Shown only for providers that support it (ideogram-remix, qwen-i2i). Lower = stays closer to the base image. |
| Guidance Scale | slider | varies | Prompt-adherence guidance. Shown only for providers that support it (qwen-i2i, qwen-edit). |
baseImageUrl |
image url | – | Inpaint / refine base image. Set automatically from the node’s own current result at run time (or a connected image). See Inpainting & Refine. |
maskUrl |
mask url | – | Inpaint mask (white = edit, black = keep). Produced by the in-panel Mask Painter or a Generate Mask node. |
Inputs & Outputs
Inputs (Handles v2.1):
The Generate Image node has 6 typed input handles on its left edge (color-coded pips), stacked from the bottom up: Prompt (closest to the corner) → Negative → References → Assets → Elements → Look. Click any handle pip to manage connections (jump to, disconnect, add new). Drag from a handle as usual to wire upstream nodes.
| Handle | Color | Accepts | Description |
|---|---|---|---|
prompt |
pink | Text producers (Text Prompt, AI Writer, Generate Script, Combine Text, Image-to-Text, Generate Text) + all parameter pickers (as {Label} variable sources) |
Main prompt text. Picker values are also available as {Picker Label} in the prompt regardless of wiring — variable substitution is workflow-wide. |
negative |
red | Text producers | “Avoid” string — what the model should not generate. Useful for sharing one negative across many Generate Image nodes. |
references |
cyan | Image producers (Upload Image, Generate Image, Edit Image, Image-to-Image, Modify Image, Upscale, Remove Background) | Reference images for the provider. Order matters — provider semantics depend on the order of refs. |
assets |
rose | Identity nodes (Character, Location, Object, Face) | Identity-locked refs with @mention expansion and canonical descriptions. (Renamed from subjects in v2.1.) |
elements |
indigo | “Subject / Object” family pickers (Person, Pose, Animal, Vehicle, Weapon, Furniture, Material, Held-Prop, Styling, Instrumentation) | Pickers wired here tail-append their value to the prompt at execution time. |
look |
indigo | “Look” + “Camera” family pickers (Style, Lens, Lighting, Color Look, Framing, Camera Format, Photographer, Aesthetic, Era, Photo Genre, Mood, Atmosphere, Backdrop, Exposure Settings, Render Quality, Composition Effects, Post-Process Effects, Tone, Camera Motion, Temporal, Transition, Character FX) | Pickers wired here tail-append their value to the prompt — same runtime path as the legacy cinematography handle. |
Variable defaults: any {Label} reference can carry a fallback with || — {Label || default}. If nothing provides Label, the trimmed default is used; e.g. generate a {person || man} running becomes “generate a man running” when no person is wired, or uses the wired/picked value when it is. {person || } (empty after ||) resolves to nothing when unset; plain {person} (no ||) stays literal when unset.
Variable highlighting: in the prompt editor (config panel and the ⌘E prompt modal), {Label} variables are highlighted — cyan when a matching upstream node is wired (or for built-in template variables like {userPrompt}), amber when nothing upstream provides that label yet. Amber means “nothing wired”, not “will fail”: a {Label || default} variable still resolves to its default at run time. Inside {Label || default}, the default text renders bright when it will actually be injected (nothing wired, or the wired node’s text is empty) and greyed-out with a strikethrough when a wired node’s value overrides it.
Outputs:
image(cyan) — generated image URL. Shares the References color since both are “image” type.
Managing connections: Click any handle pip to open a popover that lists currently connected nodes. Each row has a “jump to” button (centers the canvas on the upstream node) and a “disconnect” button. The popover also has an “Add new” button that opens a filtered node picker showing only types compatible with that handle.
Connection validation: Dropping an incompatible connection (e.g., a Character node onto the Prompt handle) is rejected — the line flashes and the connection is not created. Type-aware drop targets help guide users to the right port.
Visual states: Pips have three modes — idle (hollow ring in border color, dim brand-color icon), connecting (drag in progress; this pip is the source OR a valid compatible target → hollow ring in brand color, full-opacity icon), and connected (solid brand-color fill, white icon, count badge revealed on hover/select when ≥2 connections).
Legacy handles are migrated automatically when workflows load:
in→ classified by upstream type: text →prompt, image →references, identity →assets, picker →lookorelements(by family).cinematography/style→lookorelementsbased on the source picker’s family.subjects→assets.
The migration runs on the frontend (loadWorkflow) plus three defensive backend sites (POST/PATCH, MCP import/update, orchestrator pre-execution) so the rewrite reaches the DB even for workflows touched by external clients.
Supported Providers
| Provider | Label | Description | Aspect Ratios |
|---|---|---|---|
| nano-banana | Nano Banana | Fast drafts, iteration, storyboards | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 5:4, 4:5, 21:9 |
| nano-banana-pro | Nano Banana Pro | Higher detail, production-ready images | Same as Nano Banana |
| nano-banana-2 | Nano Banana 2 | Updated Nano Banana with web grounding | Same as Nano Banana |
| nano-banana-2-lite | Nano Banana 2 Lite | Fast, low-cost 1K drafts and iteration (Gemini 3.1 Flash-Lite). Flat 2 credits per image — no resolution tiers. | auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 4:5, 5:4, 21:9, 4:1, 1:4, 8:1, 1:8 |
| grok | Grok | Creative and stylized imagery | 1:1, 16:9, 9:16, 3:2, 2:3 |
| flux | Flux | Photorealistic, highest quality output | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3 |
| flux-flex | Flux Flex | Flexible Flux, fast generation | Same as Flux |
| flux-kontext | Flux Kontext | Context-aware generation and editing | 1:1, 16:9, 9:16, 4:3, 3:4, 21:9 |
| flux-kontext-max | Flux Kontext Max | Highest quality Kontext generation | Same as Flux Kontext |
| gpt-image | GPT Image | Text rendering, complex compositions | 1:1, 3:2, 2:3 |
| gpt-image-2 | GPT Image 2 | Higher resolution GPT Image; supports 1K/2K/4K | 1:1, 16:9, 9:16, 4:3, 3:4 |
| imagen4 | Imagen 4 | Google’s latest, strong prompt adherence | 1:1, 16:9, 9:16, 4:3, 3:4 |
| imagen4-fast | Imagen 4 Fast | Fast Imagen, lower latency | Same as Imagen 4 |
| imagen4-ultra | Imagen 4 Ultra | Highest quality Google image gen | Same as Imagen 4 |
| ideogram-v3 | Ideogram V3 | Fast text-to-image | 1:1, 16:9, 9:16, 4:3, 3:4 |
| qwen | Qwen | Versatile, good at diverse styles | 1:1, 16:9, 9:16, 4:3, 3:4 |
| seedream | Seedream | Photorealistic, high detail | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9 |
| seedream-5-lite | Seedream 5 Lite | Latest Seedream, fast and sharp | Same as Seedream |
| seedream-5-pro | Seedream 5 Pro | Flagship Seedream, best instruction following. Quality-tiered pricing: 3 credits at basic (1K output) / 6 credits at high (2K output). | Same as Seedream |
| z-image | Z-Image | Fast, lightweight generation | 1:1, 16:9, 9:16, 4:3, 3:4 |
| wan-2.7 | Wan 2.7 | Text-to-image, 1K/2K/4K resolution, up to 9 optional reference images | 1:1, 16:9, 9:16, 4:3, 3:4, 21:9, 8:1, 1:8 |
| wan-2.7-pro | Wan 2.7 Pro | Higher quality text-to-image, 1K/2K/4K resolution | 1:1, 16:9, 9:16, 4:3, 3:4, 21:9, 8:1, 1:8 |
| flux-2-klein | Flux 2 Klein (Open) | BFL Flux 2 9B Klein via Replicate — fast, no safety filter. Resolution 0.5 / 1 / 2 / 4 MP (default 1 MP). 1 credit at 1 MP, scaling with resolution. | Same as Flux |
| flux-2-pro | Flux 2 Pro (Safety Tolerance) | BFL Flux 2 Pro flagship via Replicate — safety_tolerance pinned to 5 (max for Pro). Resolution 0.5 / 1 / 2 / 4 MP (default 2 MP). Per-megapixel pricing: 3 credits at 2 MP. |
Same as Flux |
| flux-2-max | Flux 2 Max (Safety Tolerance) | BFL Flux 2 Max via Replicate — safety_tolerance=5, up to 8 reference images. Resolution 0.5 / 1 / 2 / 4 MP (default 2 MP). Per-megapixel pricing: 7 credits at 2 MP (0 refs), 14 credits at 4 MP (0 refs), scaling with resolution and refs. |
Same as Flux |
Inpainting & Refine
Once a Generate Image node has a result, you can edit it in place — re-render a painted region (inpaint) or refine the whole image (image-to-image) — without adding a separate Edit Image / Modify Image node.
Inpaint (masked edit)
When the node has a current result, open its config panel and scroll to the Inpainting Mask painter. Paint over the area you want to change:
- White = edit, black = keep. Only the masked area is regenerated; everything outside the mask stays pixel-identical to the original.
- Run the node again with a new prompt describing the change. The provider re-renders, and the masked region of the new image is composited back over the original.
This works on every image provider, not just one model. A server-side composite floor restricts the change to the masked region (out = base·(1−mask) + result·mask), so even providers that have no native mask parameter produce a clean, localized edit.
Strong instruction-following editors (gpt-image, gpt-image-2, nano-banana, nano-banana-pro, nano-banana-2, nano-banana-2-lite, seedream, seedream-5-lite, seedream-5-pro, qwen, flux-kontext, flux-kontext-max) additionally get a natural-language region hint injected into the prompt (e.g. “Apply the following change only to the upper-left region…”) for better in-region results. This is automatic — no user action required. Other providers rely on the composite floor alone, which still keeps the edit localized.
The mask comes from either:
- The in-panel Mask Painter (click Edit Mask to paint or touch up), or
- A wired Generate Mask node, which auto-segments a subject from a text description (white = subject) and can seed the painter.
Refine from this result
The node also exposes a ↻ Refine from this result affordance. It takes the current result as the base for a full-image image-to-image refine (no mask) and re-runs the provider over the entire frame. Use it for whole-image iteration — “make the whole thing more cinematic”, “warmer grade”, “more detail” — where you want to evolve the image rather than surgically patch one spot.
For providers that expose them, the Strength (i2i denoising) and Guidance Scale sliders appear in the panel and let you control how far the refine moves from the base image.
Credits
An inpaint or refine edit is one generation at the provider’s normal cost — there is no extra surcharge for the mask or the composite step. The price is exactly the per-provider Generate Image cost listed in Supported Providers above (e.g. nano-banana-pro inpaint costs the same as a fresh nano-banana-pro generation).
Best Practices
- Use Nano Banana or Z-Image for rapid iteration and storyboarding due to fast generation speed.
- Use GPT Image for scenes requiring accurate text rendering (signs, labels, UI mockups).
- Append style presets rather than writing style instructions in the prompt – the system handles appending automatically.
- For models that support reference images (nano-banana, nano-banana-pro, nano-banana-2, nano-banana-2-lite), connect Character nodes upstream for consistent character appearance across shots.
- Set negative prompts for all providers to reduce unwanted artifacts. For imagen4/ideogram/qwen, the negative prompt is sent natively; for others it is appended as “Avoid:…”.
Common Use Cases
- Generating hero images for social media posts or ads.
- Creating storyboard frames from script scene descriptions.
- Producing product visualization shots with style consistency.
- Building character sheets by generating multiple angles with reference images.
- Creating background art or environment concepts for video compositions.
Tips
- Use 1K resolution and medium quality during iteration, then switch to higher settings for final output.
- The style dropdown supports a “Custom…” option for free-text style descriptions when presets are insufficient.
- When connecting a Provider parameter node upstream, it overrides the provider selection on this node, which is useful for batch-switching models across multiple Generate Image nodes.
Trained character routing (Cloud edition)
When you @mention a trained character — a character with a successful LoRA — in the prompt, this node automatically routes through the trained Flux LoRA on Replicate instead of the selected provider. The dropdown provider’s price is replaced by 2 credits/image.
Two or more trained @-mentions in one prompt fall back to the selected provider + reference-image injection (multi-character LoRA composition is Phase 2).