Models/Collections/Best Outpainting
Capability · Editing20 ModelsUpdated Sep 2026

Best Outpainting

Models that specialise in extending images beyond their original borders, generating new content that blends seamlessly with the existing scene. Useful for widening compositions, adding context, or adapting images to different aspect ratios.

The picks.Best Outpainting

TXT → IMGIMG → IMG

GPT-Image-2.5 Sunburst

Premium image generation and editing with precise control across iterative edits

$0.0152/inpaint
Run
TXT → IMGIMG → IMGEDIT

Open weights.Hosted alternatives for this stack

Open-weight models covering the same tasks as this stack, running on Runware's own optimized compute and billed on compute time. License terms vary per model — check each model page before self-hosting.

Black Forest Labs

FLUX.2 [klein] 9B KV

by Black Forest Labs

KV-cache accelerated image generation and editing for real-time multi-reference workflows

TXT → IMGIMG → IMG
from $0.00169/text-to-image
Black Forest Labs

FLUX.2 [dev]

by Black Forest Labs

FLUX.2 dev for controllable open text to image workflows

TXT → IMGIMG → IMG
from $0.009/text-to-image
RunDiffusion

Juggernaut Z Fast

by RunDiffusion

Fast iteration model for prompt testing, composition exploration, and early visual direction

TXT → IMGIMG → IMG
from $0.00169/text-to-image
RunDiffusion

Juggernaut Z

by RunDiffusion

Polished image model with stronger cinematic lighting, cleaner focus, and richer portrait detail

TXT → IMGIMG → IMG
from $0.00338/image-to-image

Common questions

Yes — FLUX.1 Fill [dev] run on Runware's own optimized compute (the platform's open-weight tier, billed on compute time). Check each model page for license terms before self-hosting.

GPT-Image-2.5 Sunburst, released September 2026 per the live catalog. Membership updates automatically as the catalog publishes new models to this collection.

Production notes

Every price on this page is the model's published rate from the live Runware catalog, using the cheapest listed configuration unless stated otherwise. Prices vary with resolution, duration, quality tier, or token volume, so check the pricing table on each model page before estimating unit economics.

The Runware catalog does not publish per-model latency figures, so this page does not quote end-to-end timings. Where a model's own description commits to speed (for example sub-second generation or realtime streaming), that claim is repeated here. For anything else, benchmark the exact models in the Playground with your own payload sizes before committing to an SLA.

Models are addressed by versioned AIR identifiers, so a workflow pinned to specific model versions keeps producing the same behaviour as new versions ship. Adopt upgrades deliberately by re-running your evaluation set against the new version before switching production traffic.

About this collection

Models that specialise in extending images beyond their original borders, generating new content that blends seamlessly with the existing scene. Useful for widening compositions, adding context, or adapting images to different aspect ratios.

Learn: how outpainting works

Membership comes directly from the Runware catalog: the 20 models on this page are the live catalog's own membership for the "Best Outpainting" collection. Names, descriptions, pricing, capability chips, samples, and guides are all read live from the catalog — nothing here is hand-curated.

Model guides.Learn how to use the stack

GPT-Image-2.5 Sunburst

Precision editing

How to use GPT-Image-2.5 Sunburst for detailed and repeated edits: what the longer generation time buys, and when to reach for it instead of Flare.

Read the guide →
GPT-Image-2.5 Flare

Editing images

How to edit an image with GPT-Image-2.5 Flare: one source, one written instruction, and the composition, lighting and detail the model holds while it changes what you named.

Read the guide →
GPT-Image-2.5 Flare

Iterative editing

How to run a chain of edits with GPT-Image-2.5 Flare: feeding each result back as the next source, what accumulates across passes, and when to restate instead of chain.

Read the guide →
GPT-Image-2.5 Flare

Prompting

How to prompt GPT-Image-2.5 Flare: writing a brief it can plan a layout from, pinning counts and positions, and choosing a size from its custom dimension envelope.

Read the guide →
GPT-Image-2.5 Flare

Quality levels

How to set rendering effort on GPT-Image-2.5 Flare with settings.quality: what each level changes, what it costs, and which subjects are worth the top of the ladder.

Read the guide →
GPT-Image-2.5 Flare

Subject consistency

How to keep one product or character recognisable across new scenes with GPT-Image-2.5 Flare: how many reference images to send, and how to say what each one is for.

Read the guide →
GPT-Image-2.5 Flare

Transparent backgrounds

How to generate cut-out assets with GPT-Image-2.5 Flare: settings.background, the output format it forces, and prompting for edges that survive compositing.

Read the guide →
GPT Image 2

Prompting

How to write prompts for GPT Image 2 across the cases the model handles unusually well: photorealism, accurate text, world-knowledge composition, and multi-image editing workflows.

Read the guide →
Muse Image

Editing images

How to edit an image with Muse Image: passing one source image, targeting a region in words, removing objects, restoring old photos, and refining a result across passes.

Read the guide →
Muse Image

Grounding images with web and image search

How to ground Muse Image in real facts and real references with settings.webSearch and settings.imageSearch, and when to switch the lookups off.

Read the guide →
Muse Image

Building infographics and charts

How to build data-accurate charts and infographics with Muse Image: what settings.shell does, how to write your figures into the prompt, and when to switch it off.

Read the guide →
Muse Image

Composing with multiple reference images

How to build one image out of up to ten reference images with Muse Image: giving each reference a job in the prompt, and sizing the output with resolution 2K.

Read the guide →
Muse Image

Prompting

How to prompt Muse Image: writing a brief it can plan a layout from, setting the thinking level, picking one of the eight size pairs, and working without a seed.

Read the guide →
Muse Image

Rendering exact text

How to render exact, legible copy inside an image with Muse Image: quoting the literal string, keeping it short, directing the type, and landing multi-element layouts.

Read the guide →
Seedream 5.0 Pro

Multilingual text rendering

How to prompt Seedream 5.0 Pro for accurate in-image text across 15 native languages, from French posters with accented characters to Arabic, Thai, Korean, and Japanese scripts.

Read the guide →
Seedream 5.0 Pro

Prompting

How to prompt Seedream 5.0 Pro for text-to-image, reference-guided editing, and multi-image fusion in commercial workflows: campaign posters, product variants, and editorial still-life.

Read the guide →
Nano Banana 2

Keeping characters and products consistent

How to use Nano Banana 2 reference images to keep the same character or product identical across new scenes and styles.

Read the guide →
Nano Banana 2

Grounded generation with web and image search

How to generate images from real-time information with Nano Banana 2 using web and image search grounding via providerSettings.google.

Read the guide →
Nano Banana 2

Combining multiple images into one composition

How to merge several reference images, a product, a subject, a backdrop, or a style, into a single coherent image with Nano Banana 2.

Read the guide →
Nano Banana 2

Prompting

How to write prompts for Nano Banana 2: detailed scene descriptions, structured layering, legible text rendering, and thinking-level control.

Read the guide →
FLUX Outpainting

Extending images

How to extend an image past its original frame with FLUX Outpainting. No prompt, no mask, just more canvas around what is already there.

Read the guide →
Qwen-Image-3.0

Dense layouts and information design

How to generate infographics, comparison grids, newspaper pages, and interface mockups with Qwen Image 3.0 by spending its long prompt budget on every panel.

Read the guide →
Qwen-Image-3.0

Prompt extension with Qwen Image 3.0

How promptExtend works on Qwen Image 3.0: what the LLM rewrite adds to a short prompt, how the direct and agent modes differ, and why extension and seeds don't mix.

Read the guide →
Qwen-Image-3.0

Prompting Qwen Image 3.0

How to prompt Qwen Image 3.0, from sizing inside its pixel budget to layering a scene description, steering with negativePrompt, and locking a result with a seed.

Read the guide →
Qwen-Image-3.0

Editing and composing with reference images

How to use reference images on Qwen Image 3.0 to recolour a packshot, carry a product into a new scene, or stage two products together in one shot.

Read the guide →
Qwen-Image-3.0

Text and typography with Qwen Image 3.0

How to render exact copy with Qwen Image 3.0: quoting the strings you need, building a type hierarchy, setting Chinese and bilingual layouts, and sizing for print.

Read the guide →
Seedream 4.5

Prompting for layered, high-resolution scenes

How to write prompts for Seedream 4.5, from short interpretive prompts to layered scene descriptions, with legible text rendering at 2K to 4K.

Read the guide →
Riverflow 2.5 Pro

The custom scoring rubric

How to use scoringPrompt and scoringRubric on Sourceful Riverflow 2.5 Pro to drive different production workflows from the same brand inputs.

Read the guide →