Krea Release Notes

Edits in under 8 seconds at native 2K, with products and characters that stay consistent.

The Krea Team

Editing models got good enough for production work. So why does editing still feel slow?

Over the past year, image editing crossed a quality line. Teams now use it to put products in new scenes, swap materials and colors, and make campaign variants at volume. The catch is that the best editing models also got slower and more expensive. A minute and a quarter of a dollar per edit is fine for one hero shot. For a whole catalog, or for trying ten ideas before lunch, it adds up fast.

Today we’re releasing Krea 3, our new image editing model, and we built it for the other side of that trade. Most edits come back in under 8 seconds, end to end, at native 2K. It costs $0.06 per image at 2K.

Krea 3 also leaves alone what you didn’t ask it to touch. Change the setting around a product and the label stays sharp. Give it a face and an outfit, and the person in the next image is still the same person. It takes up to 6 reference images per edit.

Krea 3 is live today on krea.ai for our 30 million users, and through fal, Hedra, Together AI, Nous Research, OpenRouter and Replicate.

"Editing models are already used across e-commerce, film and advertising, but most of their potential is still held back by speed. Krea 3 removes the tradeoff between speed and quality, delivering high-quality edits in under 8 seconds, end-to-end, at 2K native resolution."

— Víctor Perez, co-founder and CEO of Krea

How Krea 3 compares

KREA 3 VS. OTHER EDITING MODELS

Krea 3 compared with Nano Banana Pro and GPT Image 2

KREA 3 NANO BANANA PRO GPT IMAGE 2 Time per edit Under 8 s 33 s 90 s Price per image $0.06 at 2K $0.135 $0.22

Krea 3 at 2K · Nano Banana Pro and GPT Image 2: median time from request to finished image for edit jobs on Krea, Sep 24 to Oct 1, 2026, queue included · list prices per image, without image references

All images edited with Krea 3.

Your product stays your product

The hardest part of an edit is everything you didn’t ask for. Krea 3 keeps the product as it is, down to the label and the logo, and builds a new scene around it. A packshot on white becomes a campaign photo.

For e-commerce and marketing teams, one product photo can become a lifestyle shot or an on-model shot without the product drifting.

Precision editing

Ask Krea 3 to change one thing and it changes one thing. In the room below we swapped the sofa, the chairs and the table. The rug, the view and the woman reading in the corner are still there.

That matters when you need to update a single product or label and keep the rest of an approved image untouched.

“Replace only the seating in image 1 with the sofa, chairs and table from images 2 to 4. Keep the rug, the room and the reading woman.”

Prompt shortened. One scene and three product references. Drag to compare. Krea 3, 2K.

“Turn all these into photorealistic renders, using the K3 Kola label. Keep all the specs and designs 100% accurate.”

1 · Input: the technical drawing

Fast enough to keep going

Speed changes how editing feels. At under 8 seconds an edit, you stop planning prompts and start trying things. While another model is still working on one image, you’ve already looked at four or five.

Krea 3 and Nano Banana Pro on the same perfume edit.

SECONDS PER EDIT

• Krea 3
• under 8 s
• Nano Banana 2
• 27 s
• Nano Banana Pro
• 33 s
• GPT Image 2
• 90 s

Krea 3 at 2K: under 8 seconds per edit · other models: median time from request to finished image for edit jobs on Krea, Sep 24 to Oct 1, 2026, queue included

"For years, image models have made creators choose between the best quality and the speed to actually iterate. Krea 3 removes that tradeoff. When a top-quality edit comes back fast enough to try the next idea right away, the model stops being a step in the workflow and becomes the workflow."

— Justine Moore, Partner at a16z

Materials, light and style

Krea 3 can follow a detailed brief. Here it took a line drawing and a flat palette of six colors and turned them into a finished room, with each color where the brief put it. The camera and the architecture didn’t move.

It also has Krea 2’s eye for style, so it works on paintings, vector art and ink drawings and keeps them in their own medium.

• Line drawing
• Krea 3
• Colour palette
• A
• Aubergine panelling
• B
• Green stone floor
• C
• Cream stone
• D
• Buff brick vaults
• E
• Ochre upholstery
• F
• Aged brass

“Materialize the hidden-line restaurant as one architectural photograph. Take every color from the A–F palette: panels, floor, vaults, upholstery and brass.”

Prompt shortened. Line drawing and a flat color palette. Drag to compare. Krea 3, 2K.

The same character, in every image

Krea 3 keeps people and characters consistent too. Give it a few references and it can put the same cast on a new street, in a new pose or under new light.

In fashion and film, that’s the difference between one good image and a set you can use. The campaign keeps its model from the first shot to the last. For a consistent look across a series, you can also add style references.

“Editorial street-style photograph on 35mm film. Reproduce the four characters from the references exactly. Only their poses change.”

Prompt shortened. Four character references. Krea 3, 2K, 16:9.

Structure your prompts for better results

Most of the prompts behind these examples follow the same pattern:

• Start with what stays. “Keep the product exactly as it is” works, and it helps to name what matters, like the label or the logo.
• Then describe the change the way a photographer would: the scene, the light, the camera.
• With several images, say what each one is for, for example “image 1 is the room, image 2 is the sofa”.
• Use “only” when the edit should touch one thing: “Remove only the woman in the red coat.”

From a sketch to a finished image

Sometimes it’s quicker to draw an idea than to describe it. A marker sketch, a moodboard or an old polaroid already has the design in it, and Krea 3 follows it closely to make a finished photo.

Add a line about the material and the light, and an architect or a product designer can see a room or an object before it’s built.

Krea 3 in the API

Krea 3 is in the Krea API, and our partners serve it too. Teams already use it to:

• turn a phone snapshot of a product into a studio packshot, or into a set of colorways
• localize a poster, or adapt one ad to a new format
• try materials and light on a building before anything is built

Pixelcut put early versions of Krea 3 in front of its users:

"We've been testing K3 since its early checkpoints, and the Krea team has done an incredible job. We put it in front of real Pixelcut users, and the results were very impressive. What stood out most was the lighting. The product shots look like they were lit by a professional photographer, not generated by AI. Most of our customers are small businesses that can't afford a studio shoot for every product. K3 gives them that same beautiful, studio-quality lighting while staying true to the original product. That's exactly what they need to sell online."

— Dominique Yahyavi, Co-Founder and CEO of Pixelcut

Pricing and availability

Krea 3 is on krea.ai today, at $0.06 per image at 2K and $0.03 at 1K. At that price, it makes sense to run it on every image in a catalog.

COST AT VOLUME

Monthly cost of 100,000 edits at list price

Krea 3 $6,000/mo $0.06 per image Nano Banana Pro $13,500/mo $0.135 per image GPT Image 2 $22,000/mo $0.22 per image

monthly cost of 100,000 edits at list price per image · Krea 3 at 2K, without image references

Enterprise teams can talk to us about access.

What’s next

Krea 3 isn’t real time yet. Our fastest setup finishes an edit in about 4 to 5 seconds, and we want to get that lower.

We also want more resolution for less compute. Training at 2K was one of the biggest wins this cycle. Next we’ll look at architectures that handle high resolution more cheaply.

And we want Krea 3 to understand more ways of asking. Sometimes it’s easier to circle something, or to write the instruction on the image, than to put it into words. We’re building the training data for that now.

Frequently asked questions

• What is Krea 3?
• How much does Krea 3 cost?
• How many reference images can I use?
• What resolution does Krea 3 support?
• Where can I use Krea 3?

Try Krea 3

Edit an image in under 8 seconds.

Original source

Seedance 2.5 is ByteDance’s video-generation model for text-to-video, image-to-video, and reference-guided video, with optional audio generated alongside the picture. Seedance 2.5 is available on Krea for text-led generation and reference-guided generation.

The important change is not a longer list of settings. The reported roughly 20% gain in prompt adherence still leaves identity-dependent work reliant on supplied character sheets, product photographs, and location references.

Seedance 2.5 assigns separate input roles to identity, clip endpoints, and on-screen action. References preserve identity, while prompts describe the on-screen action. Start and end frames control the clip’s boundaries. Seedance 2.5 is most useful when specific people, products, and locations must persist across a longer generation, because Krea expands the reference and duration ceilings while keeping the prompt focused on action.

Key takeaways

• Use separate reference assets for each face, product, and location so fixed assets remain recognizable throughout generation.
• Seedance 2.5 provides multimodal reference capacity for up to 50 assets in a single Krea API request.
• Choose Seedance 2.0 when native 1080p or 4K output matters more than a 30-second clip or larger reference capacity.
• Name each shot in a long prompt so the model has an explicit sequence of events and framing changes to follow.

What Is Seedance 2.5 Used For?

Seedance 2.5 combines motion generation and optional native audio in one video request. Its generate_audio control can produce an audio track in the same pass as the picture, rather than requiring sound to be synced afterward. That makes it useful when room tone, foley, or lip movement belongs to the shot itself.

Krea’s model page also describes an extended beta mode that can reach 180 seconds. Standard request limits matter more for routine production, yet the beta mode points toward longer-form generation rather than isolated short clips.

Seedance 2.5 also provides a targeted correction path for local defects. Krea’s model page and Framite’s review describe region-level editing for a face, object, or background without regenerating the complete clip. When the defect is confined to one part of a scene, revision can focus on that region instead of restarting the sequence.

Seedance 2.5’s Actual Limits on Krea

Krea’s API gives Seedance 2.5 its largest increase in reference capacity and standard clip length. The model accepts up to 30 reference_images, 10 reference_videos, and 10 reference_audios in one request, for 50 multimodal references overall. Its duration ranges from 4 to 30 seconds, and its native render tiers are 480p and 720p. Those limits let you keep a larger set of visual and sound inputs within one sequence rather than dividing continuity-sensitive work into many smaller clips.

You can use these controls to set a clip’s framing and reproduce a generation. Seedance 2.5 supports six aspect ratios, including 16:9, 1:1, and 9:16. Composition controls include one start_image, one end_image, and an integer seed. You can also attach up to 12 named image or video effects and turn enhance_prompt on or off. Only prompt is required; generate_audio defaults to false and every other field has a default. You can therefore lock a clip’s boundaries and repeat an experiment while the prompt directs the movement and event.

The comparison with Seedance 2.0 is a trade between working headroom and native resolution. Krea’s Seedance 2.0 schema supports 15 references in total, with clip durations from 4 to 15 seconds. Seedance 2.0 adds native 1080p and 4K output, with an upscale flag that can take a finished clip to 8K. It shares the same aspect-ratio and audio controls, and it also supports start and end images. Choose 2.5 when continuity across more inputs or more time sets the constraint; choose 2.0 when native 1080p or 4K delivery sets it.

How Reference-Guided Generation Works in Seedance 2.5

Text Defines the Event, Not the Exact Assets

A detailed scene prompt can create the right type of scene without creating the exact character, product, or location you intend. A text-only Seedance 2.5 prompt describing a woman in a green field jacket entering a rainy neon noodle bar produced a different woman in an American-style diner with vinyl stools and a plain grey tumbler. The prompt supplied mood and action while leaving the woman, bar, and mug without identity constraints.

Give Each Fixed Asset Its Own Reference

A multi-angle character sheet gives the model identity information that prose cannot reliably preserve. The character reference is a three-panel sheet with full-body, front, and right-profile views. The woman is defined by her moss-green field jacket. Those views give the model useful coverage when she turns or appears at different shot distances.

The character reference constrained the character alone, while the bar and mug remained unconstrained. With only the character sheet attached to the same prompt, Seedance 2.5 preserved her face, hairline, and green field jacket while producing a generic bar and a plain white mug. The practical rule follows directly: if an asset’s specifics matter, give that asset its own input.

A product needs a separate reference when its material, form, and packaging details are part of the deliverable. Here, the product input is a studio image of a speckled terracotta travel mug with a brushed copper screw lid and matte black silicone grip band. Supplying the image turns the mug into a visual constraint instead of asking the prompt to reconstruct several small details.

A location reference fixes the physical setting so the prompt can direct the event inside it. The location is an empty late-night noodle bar defined by a pale wood counter, red-and-blue neon signage, and rain on the front window. Once the room is supplied, the text can focus on the entrance, movement, and interaction.

Three targeted references can preserve a character, product, and setting together in one generation. In an eight-second Seedance 2.5 generation using all three inputs, the recognizable woman places the terracotta mug, including its copper lid and black grip band, on the counter of the neon, rain-streaked noodle bar. The gain comes from assigning every non-negotiable element a source asset.

That three-reference result does not make Seedance 2.5 automatically more faithful than Seedance 2.0. The same prompt and three references run through Seedance 2.0 also retained the woman, mug, and noodle bar at eight seconds. At this modest scale, both models hold the required assets; 2.5 becomes the better fit when a project exceeds Seedance 2.0’s reference-image or duration ceiling.

Start and End Images Control the Destination

Frame inputs set a clip’s visual boundaries, while references preserve its assets. The end-frame input here is an edited version of the noodle bar at mid-morning, with neon off and rain gone, while the counter, stools, and camera position remain unchanged. Use this pair when the destination of a transformation matters as much as the opening composition.

A pinned first and last frame gives Seedance 2.5 an explicit visual journey to generate between. With the night bar set as start_image, the morning bar set as end_image, and a locked-off prompt describing rain stopping and daylight rising, the model generated the transition without people in frame. This approach fits time-of-day changes, reveals, and before-and-after scenes because the ending is specified rather than invented.

Audio and Shot Lists Extend the Same Logic

Audio is a request-level choice that needs no change to the references. A generation with audio enabled and the character and product references attached shows the woman lifting the copper lid off the mug, with rain and room tone beneath the action.

A long generation needs an explicit shot progression to become a sequence rather than an extended moment. The 20-second Seedance 2.5 request included three references and audio. Its four numbered shots move from a wide entry through a medium counter view and a close-up of the lid to a final wide view from behind. Numbering gives the model an order to follow while the references carry the woman, mug, and room across changes in framing.

Who Should Use Seedance 2.5?

Ad teams can generate campaign cuts around the same SKU while keeping the product and presenter recognizable. A product reference prevents packaging from drifting while a team generates several cuts around the same SKU. That matters when recognition of the item is more valuable than a newly invented object in every version.

Filmmakers and previs teams can use Seedance 2.5 to carry a character through a location and across planned shots. Its 30-second standard duration can accommodate four to five shots in one generation when the prompt names each shot. Multi-shot generations reduce handoffs that can introduce visual mismatches between planned shots.

Ecommerce teams can use a single product image to stage the same item in several contexts. A 30-second generation can reduce the clip joins where product, costume, or set continuity drifts. The return is highest when a fixed SKU or visual identity matters more than generating a different-looking product for each setting.

Seedance 2.5 Limitations to Plan Around

Render resolution is the clearest reason to choose Seedance 2.0 instead. Although Seedance 2.5 provides more reference and duration headroom, choose Seedance 2.0 when native 1080p or 4K output and its built-in upscale path outweigh those gains. Reference capacity does not override the delivery requirement.

The five- to eight-second Seedance 2.5 renders in this sequence took roughly two to three and a half minutes each, and a weak output means paying that cycle again. Small text and fine logo details remain weak points, while wardrobe and props hold more reliably. Budget time for reruns and write clear numbered shots, because a long vague prompt produces a long vague clip.

How to Get Started With Seedance 2.5 on Krea

Seedance 2.5 is available on Krea’s model page, in the Krea video generator, and through POST /generate/video/bytedance/seedance-2-5 in Krea’s API. Krea’s video documentation covers start and end frames and identifies models with native audio.

Start with one simple scene and attach a reference for the one thing that cannot drift. Keep the prompt focused on action, then add a reference or motion control for the element that drifts in the output.

When the woman, terracotta mug, and rain-lit noodle bar all need to remain the same across a sequence, assign each one a reference before asking the model to move them. References provide fixed identities; the prompt directs the action in each shot.

FAQ

Frequently asked questions

What exactly is Seedance 2.5 on Krea?

What’s the main improvement in Seedance 2.5?

How does reference-guided generation work in Seedance 2.5?

What are Seedance 2.5’s practical limits on Krea (refs and clip length)?

When should I use Seedance 2.5 vs Seedance 2.0?

Original source

Seedream 5.0 Pro is ByteDance’s new flagship image generation and editing model, and Krea is proud to be an official launch partner. This article gives a full overview of the model’s core capabilities and why it’s the strongest model to date for full image workflows.

Seedream 5.0 Pro is live on Krea starting July 8, 2026, the day of its release.

Try Seedream 5.0 Pro

Generate, edit, blend, and batch images with Seedream 5.0 Pro on Krea.

What is Seedream 5.0 Pro

Seedream 5.0 Pro is an image generation and editing model in the Seedream family. It accepts text, a single image, or multiple images, and it can produce single images or grouped image outputs. It also supports streaming output, returning each image as soon as it is ready.

It is also the first Seedream model with web-search-augmented generation, and that changes how working with it feels. This is closer to ChatGPT Image than to a classic prompt box: instead of passively following a single prompt, the model reasons through your instruction like a designer and looks things up when the work calls for it. Add what Seedream has always been known for, style consistency and cinematic scenes with extravagant detail, and 5.0 Pro becomes the strongest creative companion yet for designers, creators, and marketers.

Text-to-image

With Seedream 5.0 Pro, one strong prompt can become a polished image with clear art direction, cinematic detail, and a finished look from the start. It is well suited to high-end concepting, campaign visuals, and art-directed image creation where the prompt needs to translate into a specific visual outcome.

“Vibrant close-up editorial portrait, model with piercing gaze, wearing a sculptural hat, rich color blocking, sharp focus on eyes, shallow depth of field, Vogue magazine cover aesthetic, shot in medium format, dramatic studio lighting.”

This is the kind of prompt that benefits from a model that can hold style, composition, and mood together in one pass. The result is a ready-to-use image that feels closer to a directed shoot than a rough draft.

Image editing - Preserve Composition, Style and Texture

Seedream 5.0 Pro can transform an existing image while keeping the original structure intact. That makes it especially useful when the pose, framing, and composition are already right, but the material, lighting, or realism need a precise upgrade.

“Keep the model’s pose and the flowing shape of the liquid dress unchanged. Change the clothing material from silver metal to completely transparent clear water (or glass). Through the liquid, the model’s skin details are visible. Lighting changes from reflection to refraction.”

The strength here is control. The subject stays recognizable, the pose stays locked, and the edit focuses on the details that matter most. For creators, that means faster material swaps, cleaner art direction, and fewer compromises when a concept needs a sharper finish.

Multi-image Blending

Seedream 5.0 Pro can combine multiple references into one coherent output while preserving subject consistency across the result. That makes it a strong option when one image has the model, another has the outfit, and the final composition needs both to feel naturally unified.

“Replace the clothing in image 1 with the outfit from image 2.”

This kind of reference blending is especially valuable for outfit transfer, accessory matching, and composite scenes where people, clothing, shoes, and environments all need to stay visually consistent in one frame.

Image Sequences from One Reference

Seedream 5.0 Pro can generate a related image sequence from a single reference image, which makes it useful for character exploration, action variations, and visual development while keeping the subject recognizable from frame to frame.

“Referring to Figure 1, generate four images with characters wearing sunglasses, riding motorcycles, wearing hats, and holding lollipops”

Instead of restarting from scratch for every variation, one reference can seed a set of connected images that stay close in identity and styling. That makes it easier to explore poses, props, and moments without losing the core character.

Batch Generation for Brand Systems and Storyboards

Seedream 5.0 Pro is built for batch creation, so one prompt or one reference can become a themed set of images with shared visual logic. That is a major advantage for storyboards, campaign exploration, and brand systems where the real challenge is not making one image, but making many that belong together.

“Generate a set of four cinematic sci-fi realistic film storyboard scenes: Scene 1: An astronaut repairs a spacecraft at a space station… Scene 2: Suddenly hit by a meteorite belt… Scene 3: The astronaut dodges urgently… Scene 4: The astronaut, injured, escapes back to the spacecraft…”

“Using this LOGO as a reference, create a visual design system for an outdoor sports brand named GREEN, including packaging bags, hats, cards, lanyards, etc. Main visual tone is green, with a fun, simple, and modern style.”

This is where Seedream 5.0 Pro feels most like a flagship workflow model. It can turn a single brief into a coherent set, or a logo into a branded kit, without forcing each asset to be built in isolation.

Get started on Krea

Open Krea, select Seedream 5.0 Pro in Image Generation, add a prompt or reference, and start creating immediately. For edits, blends, sequences, and batches, Seedream 5.0 Pro is ready to help turn one idea into a polished set of images with zero friction.

Krea is the best place to work with image and video models. Seedream 5.0 Pro sits inside Krea’s full creative suite. Compare it with other image and video models on the same canvas, keep your assets in one place, and shape the workflow around the way you work.

Make the Most out of Seedream 5.0 Pro

Seedream 5.0 Pro removes some of the biggest frictions in image creation: prompt drift, reference mismatch, repetitive setup, and the manual work of making separate assets feel related. That means faster iteration when the goal is not just an image, but a system.

Creators can use it to move quickly from concept to campaign, build consistent character sets, swap outfits and accessories with continuity, produce branded packaging systems, and create storyboard-ready scene sequences that hold together across multiple frames.

In practice, that makes Seedream 5.0 Pro useful anywhere visual consistency matters. It gives teams a way to explore more directions, keep more of the original intent, and spend less time correcting the same details over and over.

FAQ

Frequently asked questions

• What is Seedream 5.0 Pro?
• When is Seedream 5.0 Pro launching, and how to use it?
• What inputs can I use with Seedream 5.0 Pro?
• Can it edit an image without changing the pose or composition?
• Does it support multi-image blending and subject-consistent composites?

Try Seedream 5.0 Pro

Advanced image generation and editing with web search and deep reasoning. Available on Krea now.

Original source

Introduction

In this technical report we introduce Krea 2: a series of foundation models designed for both wide aesthetic diversity and user creative control. We present: (1) our principles for data curation; (2) the model architectures; (3) our multi-stage training pipeline; (4) our distributed infrastructure; and (5) future work.

Sangwu Lee, Erwann Millon, Le Zhuo, Matthew Newton, Andrei Filatov, Naga Sai Abhinay Devarinti, Dazhi Zhong, Avram Djordjevic, Gabriel Menezes, Will Beddow, Titus Ebbecke, Mihai Petrescu, Owen Fahey, Gian Saß, Felix Gil, Albert Salgueda, Victor Perez

The model weights and inference are released under a permissive license.

Introduction

Over the past few years, image generation has seen remarkable progress. Diffusion and flow-matching models can generate high-resolution images, produce sharp photorealism and stable structure, render dense text, encode broad world knowledge, and follow user prompts in precise detail. These improvements have been driven by several interacting factors including scalable transformers architectures, improved captioning and text encoders, better latent representations, and pipelined post-training techniques. Yet as the field has optimized for reliability on these capabilities, many systems have converged toward a narrow set of default aesthetics. While effective production tools, this makes them less effective as engines for creative exploration, where users often need to search across styles, moods, compositions and visual directions rather than receive a single polished default.

To address these limitations, we present Krea 2, a series of foundation models focused on creative exploration. Krea 2’s models are built on the belief that image generation should be an exploratory medium: expressive enough to span many aesthetics, and controllable enough for creators to navigate them.

We built a large-scale data infrastructure and distributed training framework from scratch to curate a comprehensive pretraining dataset with broad world knowledge and style coverage.

Using this infrastructure, we train expressive models through a multi-stage pipeline spanning pretraining, midtraining, supervised finetuning (SFT), preference optimization, and reinforcement learning (RL), with each stage designed to progressively refine the model’s output distribution. We develop a simple yet performant diffusion transformer (DiT) architecture through thorough ablations. Our model incorporates several components that accelerate convergence, including iREPA, improved VAEs, and Qwen3-VL. We also integrate several architectural improvements, including grouped-query attention (GQA), sigmoid-gated attention, lightweight timestep modulation, and multilayer feature aggregation for text-encoder features, which together improve training stability and efficiency.

A strong base model is only useful if users can reliably reach the parts of its distribution they care about. In training, the model learns from rich, carefully constructed captions that describe images with dense visual detail. In practice, user inputs are often shorter, more ambiguous, and shaped by many different habits of expression. Some users describe a scene in natural language; others gesture toward a mood, a style, or a reference image. This creates a gap between the model’s learned conditioning space and the way creative intent is expressed at inference time.

To reduce this gap, we build two systems that make Krea 2 more exploratory and steerable from both text and image inputs: a prompt expander and a style-reference system. The prompt expander maps simple or underspecified user prompts into richer visual directions without overwriting the user’s intent. It is trained through a two-stage SFT and RL pipeline on top of open-source LLMs, where the objective is not only to improve image quality, but also to encourage creative variation and controllable exploration. Complementing this textual interface, the style-reference system lets users express visual intent through images when words are insufficient. It allows users to inject the style or mood of one or more reference images with minimal content leakage, while providing fine-grained control over style strength and weighted style mixing.

Together, these components define Krea 2 as a foundation model for exploratory generation. Instead of optimizing only for a single polished default, Krea 2 is designed to expose a broad visual space and give users practical ways to move through it, using both text and image-based control. Krea 2 is among the top 10 models on the the Artificial Analysis leaderboard for text-to-image, and scores 2nd place among models from independent labs. Krea 2 serves as a comprehensive baseline and enables a creative generative experience while maintaining competitive performance.

[The report continues with detailed sections on Data Curation Principles, Captioning, Architecture, Optimization, Training Pipeline, Prompt Expansion, Style Reference System, Training Infrastructure, Systems Infrastructure, Observability, Lessons Learned, Filesystem and Checkpointing, Data Infrastructure, Discussion and Future Work, and Conclusion.]

Conclusion

We presented Krea 2, our first foundation-model series built for creative exploration. In this technical report, we shared the infrastructure, data systems, training pipeline, and research choices behind the model family. We believe foundation image models are still in their early stages, and we look forward to sharing more of our research.

Join us at Krea

We're building the future of creative AI. Come work with us.

Original source

By the Krea Team.

Krea 2 now gives you more control before the image is generated. Generative Sliders let you shape the model’s creative direction while keeping your original prompt intact, so you can explore different outcomes without rewriting the same idea over and over.

Open the controls panel in the Krea 2 image tool to adjust Intensity, Complexity, and Movement, choose a Creativity mode, randomize settings for exploration, or reset everything back to neutral.

Move a single setting and watch Krea 2 shift the result while the prompt stays steady.

What Generative Sliders Control

The Generative Sliders panel gives you direct control over four parts of the generation process:

Control | What it changes
Intensity | Moves from quieter, more muted images to more strongly stylized images.
Complexity | Moves from simpler, more minimal compositions to denser, more visually complex images.
Movement | Moves from more static images to more dynamic compositions with stronger camera angle, pose, and motion energy.
Creativity | Controls how much Krea expands or interprets your prompt before generation.

Intensity, Complexity, and Movement are centered Generative Sliders. A value of 0 is neutral. Moving left reduces that quality; moving right increases it.

See Generative Sliders In Action

Keep the prompt steady and move one slider at a time. These examples show how the Movement and Complexity sliders can change the generated image while preserving the core idea.

“cute poodle, city street, colorful illustration, playful composition”
Movement slider · -100, -50, 0, 70, 100

“illustrated cafe table with a croissant, coffee cup, and oversized vase of wild flowers”
Complexity slider · -100, -50, 0, 70, 100

Creativity Modes

Use Raw when your prompt is already precise. Use Low or Medium when you want Krea 2 to add useful visual detail without drifting too far. Use High when you want the model to explore the idea more aggressively.

Try Random Mode

Random mode changes the slider settings each time you submit a generation.
It is useful when you want to explore the shape of an idea quickly. Turn it on, generate a few results, and look for the direction that feels closest. Once you find something interesting, turn Random mode off and fine-tune the individual sliders from there.

A Few Starting Points

For clean design, icons, and editorial illustration, try lowering Complexity and keeping Movement near neutral.
For cinematic images, fashion, worlds, or expressive character work, try raising Intensity and adding a small amount of Movement.
For precise prompts, set Creativity to Raw or Low. For loose prompts, set Creativity to Medium or High and let Krea 2 build more of the visual language around your idea.

Try Generative Sliders

Open Krea 2 and use Generative Sliders to shape your next image generation.

Original source

By the Krea Team. Last updated June 2026.

Introducing Krea 2 Turbo.

Generate high-quality images in just 2 seconds with a faster Krea 2 experience, compatible with style references, moodboards, and LoRAs. You can try it for free in Krea.

What is Krea 2 Turbo?

Krea 2 Turbo is a faster version of Krea 2. It is designed to keep as many of the original model’s capabilities as possible while running multiple times faster.

That means you can stay inside the Krea 2 workflow, use the same creative controls, and get visual feedback much sooner. Turbo is especially useful when you want to explore an idea quickly before spending more time refining the final direction.

Built for faster creative loops

Image generation is not only about the final output. A lot of the creative work happens while you are testing prompts, changing references, comparing compositions, and deciding which direction is worth pursuing.

Krea 2 Turbo makes that loop faster. It is a good fit for rapid ideation, early concept work, moodboard exploration, product mood passes, art direction, and prompt experimentation.

Compatible with Krea workflows

Krea 2 Turbo works with style references, moodboards, and LoRAs, so you can use it in the same creative workflows you already use with Krea 2.

Because Turbo is optimized for speed, Krea 2 Medium and Krea 2 Large are still the stronger choices when exact style adherence or final-image polish matters most. Turbo is for the moments when you want to move quickly, see more options, and keep momentum.

Try Krea 2 Turbo

Generate high-quality images in just 2 seconds with Krea 2 Turbo.

Original source

By the Krea Team.

Last updated May 2026.

Krea Train lets creators teach a model a repeatable visual language: a brand style, a character, a product, a material study, or a personal subject. We are bringing that workflow closer to Krea 2.

Krea 2 LoRA training is starting as a closed beta inside Train. During the beta, selected creators and teams can train LoRAs for Krea 2 Medium and Krea 2 Large, use them in Image, and choose whether a trained style stays private or becomes a public LoRA other people can discover and reuse.

Open Train

Build a custom style, character, or object model from your own dataset.

What is a public LoRA?

A LoRA is a lightweight custom model trained on a focused dataset. Instead of rewriting a long prompt every time you want a specific look, object, or character, you train that concept once and reuse it as a style layer in generation.

A public LoRA is the same idea, made shareable. You can keep trained LoRAs private for personal or workspace use, or make selected LoRAs public so collaborators, communities, and future Krea workflows can build from the same visual identity.

Why Krea 2 LoRAs matter

Krea 2 is built for stronger taste control, sharper image quality, and a more flexible relationship between prompts and visual references. LoRA training adds another layer: persistent memory for the things you care about most.

For a designer, that might be a product line or campaign style. For a filmmaker, it might be a character or world treatment. For an architecture or interior team, it might be a material palette, rendering language, or office-specific presentation style. The point is not just to generate one good image, but to make a visual system reusable.

What you can train

Krea Train supports several common training intents:

• Styles: teach Krea a visual treatment, illustration language, material quality, lighting approach, or brand look.
• Characters: keep a person or fictional character more consistent across poses, scenes, and prompts.
• Objects: preserve a product, prop, furniture piece, or design object across new contexts.

Krea 2 LoRA training supports Style, Character, and Object modes. Krea 2 Medium and Krea 2 Large are wired as image training models, with model-specific training settings handled by the Train workflow.

Existing Train examples for styles, objects, and characters

How the beta works

The flow is intentionally simple: upload a focused set of images, choose what you are training, review or add captions when needed, and start the training job. When the LoRA is ready, it appears in Train with your other styles so you can use it in generation, reuse the dataset, update the cover, or manage its visibility.

The minimum dataset is small, but quality matters more than quantity. A cleaner set of images that repeats the same subject, style, or object usually teaches the model more clearly than a large, mixed dataset. Image limits can vary by plan, and Train will show the active limit inside the upload flow.

Private by default, public when you choose

Training is most useful when it respects the way creative teams actually work. Some LoRAs should stay private: client concepts, internal brand systems, unreleased products, or personal subjects. Others are better when shared: a public art style, a reusable community preset, or a model that helps a team create from the same visual vocabulary.

That is why Train keeps visibility as an explicit choice. A LoRA can stay private, or it can become public when you decide it is ready.

Access and availability

Train is currently available to paid Krea users with access to model training. Krea 2 LoRA training is a narrower beta: eligible users and workspaces will see Krea 2 Medium and Krea 2 Large in the Train model picker. We are using the beta to test quality, captions, training defaults, safety checks, queue behavior, and how public LoRAs should feel once more creators can use them.

As access expands, the goal is straightforward: make custom Krea 2 models easier to train, easier to reuse, and easier to share without turning the workflow into a technical chore.

Train your own visual model

Upload a focused dataset, train a style, character, or object, and use it across Krea generation tools.

Open Train

Original source

By the Krea Team. Last updated May 2026.

Moodboard Gallery just got a major expansion

We are rolling out a larger Moodboard Gallery for Krea 2 with thousands of new moodboards to explore and generate from. The goal is simple: faster style discovery and less setup before you start creating.

What is new

• Thousands of new moodboards are now available in the gallery.
• You can browse references and generate with Krea 2 from those moodboards.
• We are previewing two new selection modes: Random and Auto.

Random and Auto (preview)

These two new modes are designed to speed up early exploration:

• Random picks a moodboard for you when you want a quick unexpected direction.
• Auto selects moodboards automatically based on your generation context.

Both modes are in preview and may continue to evolve as we collect feedback.

See the update

A quick look at the expanded gallery and the new Random/Auto preview modes.

Why this matters

Moodboards are one of the fastest ways to shape visual direction in Krea 2. Expanding the gallery and automating moodboard selection helps you get to a strong starting point faster, especially during ideation.

Try Moodboard Gallery

Explore the expanded gallery and test Random and Auto in Krea 2.

Source update: @krea_ai on X.

Original source

Krea 2 is our first foundation image model

Krea 2 is our first foundation image model, trained completely from scratch to give users full control over the look, feel, and creative direction of every image they create.

Starting today, you can access Krea 2 through our API partners, such as Fal, Comfy, or Runware. We’re also launching with Nous Research, offering access to Hermes since day 0, and you can find support for Claude, OpenClaw, and Codex in our docs.

Here’s what it brings to the table:

• Aesthetic diversity – Krea 2 can generate an incredibly wide range of styles, with particular strength in artistic and expressive directions that other models tend to flatten out.
• Style transfer – Krea 2 ships with the most advanced style transfer system available. It can extract the style of one or many reference images and apply it to your outputs with precision.
• Creativity – this is an actual parameter you can tune with Krea 2. At high values, it will make the model to add aesthetic depth, interpretation, and visual richness to whatever you give it.
• Moodboards – you can pass in an entire moodboard of dozens of images and Krea 2 will understand the overall creative direction, producing outputs that align with it.

Find hundreds of examples with their respective prompts clicking the link below:

Browse the Krea 2 gallery

Hundreds of examples with the prompts that produced them.

Open the gallery

We built Krea 2 for creatives who want real control over what AI produces. We work closely with teams across creative studios, marketing and advertising agencies, fashion, gaming, and architecture — continually taking their feedback back to our research lab to push the model further for every use case. It’s a model that’s actively evolving with the people who use it.

It’s also built for exploration. You don’t always come in with a fully formed idea, and Krea 2 is designed to be a creative collaborator in those moments — something that can take a loose direction and give you back visuals that spark the next idea, rather than forcing you to specify every detail upfront.

Model variants

The Krea 2 API offers two model variants:

Krea 2 Medium and Krea 2 Large. Both support the same parameters and feature set — the differences come down to model size, training stage, and the character of the outputs they produce.

If you’re not sure which to start with, try Krea 2 Medium — it’s faster, cheaper, and handles the broadest range of use cases reliably.

Krea 2 Medium

A smaller, faster, and more cost-efficient model with extensive post-training applied. This makes its outputs especially stable and consistent across generations. Medium is particularly strong on illustration, anime, painting, and other expressive or artistic styles.

Krea 2 Large

More than twice the size of Medium, with a softer post-training applied – which gives its outputs a rawer, more textured, and flexible character. Large is the more powerful model overall – at its best, it produces results Medium can’t match. It handles expressive and artistic styles well, and shines on photorealism and “raw” looks like motion blurs, grains, or low dynamic ranges.

Features & Examples

We compiled this list of examples that you can use to test the capabilities of the model.

Aesthetic diversity

Most image models handle complex prompts well, but they tend to fall short on style — defaulting to something sharp, polished, and “safe”. That narrows the creative range you can actually get out of them.

With Krea 2, we put as much effort into how the model understands style as we did into how it understands prompts. The result is a model that can render a wide range of aesthetics – expressive, raw, niche, experimental – without falling into AI looks.

The following are a set of examples created with Krea 2 showcasing a variety of aesthetics:

“illustration of a cat riding a bicycle”

Model: Krea 2 Large

“heavily blurred dark silhouette of a head and shoulders, glowing reddish-orange center on the obscured face, thin neon lime green fire-shaped sparkles above, cool blue-grey background, heavy vintage film grain, lo-fi grunge aesthetic, dusty scratched texture”

Model: Krea 2 Large

“Close-up portrait of a woman, retro 90s anime style, large vivid blue eyes, flushed cheeks, glossy red lips, silver glitter around her eyes, single brown curl on the nose, wearing a glossy black metallic helmet with rivets, bold blue reflections, dark background, heavy film grain, saturated colors, sharp specular highlights”

Model: Krea 2 Large

Style Transfer

Krea 2 ships with the most powerful style transfer system on the market. Pass in a single reference image or combine several, and Krea 2 will extract the style and apply it to your output — letting you decide how strongly each reference shapes the final image.

The following were generated using style references:

Creativity

Creativity is an actual parameter that you can tune for Krea 2. When a prompt is short or vague, the model can fill in the missing pieces — style, composition, camera angle, color palette — adding visual depth where you haven’t specified it. The creativity parameter controls how far that expansion goes.

Set it to high and the expansion gets stronger — the model takes more creative liberty with style, mood, and aesthetics. Set it to low and the model sticks more closely to what’s in your prompt. Set it to raw and the model performs no expansion at all, rendering only what you’ve explicitly described.

Moodboards

A moodboard is the most precise way to set a visual direction with Krea 2. Moodboards are built from a group of images that share an overall creative direction — palette, texture, style, mood, or composition. You can create one in Krea and reference it when you run inference through this API.

The following examples show how activating a moodboard can transform the output of even very simple prompts.

API Setup

Create an API token from your Krea account settings. Krea 2 has two versions of the model available in the API:

Endpoints

Krea 2 Medium

https://api.krea.ai/generate/image/krea/krea-2/medium

Krea 2 Large

https://api.krea.ai/generate/image/krea/krea-2/large

Parameters

Both versions of Krea 2 support the following parameters.

• prompt (string): Required text prompt
• aspect_ratio (string): 1:1, 4:3, 3:2, 16:9, 2.35:1, 4:5, 2:3, 9:16
• resolution (string): Currently just 1K
• seed (number): Optional seed
• creativity (enum): raw, low, medium, high
• image_style_references (array): Optional style references
• moodboards (array): Optional moodboards, currently max 1
• styles (coming soon) (array): Optional trained styles (LoRAs)

Fetch completed jobs

Completed jobs can be fetched from:

https://api.krea.ai/jobs/{job_id}. You can also pass an X-Webhook-URL header to receive a POST when the job completes.

More detailed API docs are available at docs.krea.ai/developers/introduction. It covers things like the job lifecycle, webhook integrations, generating api tokens, etc.

API Examples

Below you can find a set of short guides that will show you how to use all the different features that come with Krea 2:

• Generate an image
• Use style transfer
• Adjust creative thinking
• Use moodboards

Pricing

Model type | Text-to-image | Style references | Moodboards
Medium | $0.030 | $0.035 | $0.040
Large | $0.060 | $0.065 | $0.070

Note: combining moodboards with style references will not increase the price per generation, i.e., it will be $0.04 for Medium and $0.07 for Large.

Our launch partners include Runware, Fal, Nous Research, and ComfyUI.

Original source

By the Krea Team. May 2026.

Krea 2 is our first foundation model, built completely from scratch and focused on aesthetics and creative control.

When you make an image with AI there are really two questions:
what you want in the image, and
how you want it to look.
Most models are great at the first. They handle complex prompts without breaking a sweat.
But when it comes to style they default to something polished, safe, and a little generic — the AI look.

We’ve talked before about that AI look and the barriers it creates when you’re trying to get something expressive or artistic out of a model. For Krea 2 we wanted to take it head-on.
We put as much work into how an image looks as into the model itself.
The goal was something capable of rendering almost any style — from the grainiest film photography to the cleanest studio shot, cinematic stills, illustration, digital painting, and weirder experimental territory.
And just as importantly, something you can steer, not just prompt at.

The reason matters.
The kinds of products and features we’ve been able to build at Krea have always been limited by the models we had access to.
Starting our own research lab means we can finally make the technology that lets us build creative tools that treat AI as an actual creative medium — raw, flexible, unopinionated, uncut.
Something you can break if you want to, that doesn’t quietly box you into the same handful of looks.

This post is a walkthrough of the three things that make that possible in Krea 2: open-ended exploration in the image tool, style references, and moodboards.

Watch the full deep dive

14 minutes of Krea 2 in action.

Start vague. Let the model explore.

Krea 2 doesn’t expect a fully-formed idea.
You can come into the image tool with something as bare as a cat riding a bicycle and just hit generate two or three times.
What comes back isn’t four variations on a single safe interpretation — it’s the model thinking through completely different ways that concept could be rendered.
Painting. Old VHS photography. Minimal illustration. Abstract shapes with their own internal logic.
The first round of generations becomes a kind of mood-sweep — a way to see what kinds of images even live inside this prompt, before you commit to any one of them.

This is a different posture than what most image models train you into.
You don’t have to come in with a detailed brief.
You can use the first three generations as research, find the direction you like, and then narrow from there.
It’s closer to the way an art director works — start broad, then home in — than the way most AI tools force you to write.

Tighten the prompt just a little — say, a cat riding a bicycle, retro cartoon illustration — and you still get diversity, but the cluster narrows.
All of them feel like retro cartoons; the variety lives inside that style.
Some are more complex, some more minimal, but they’re all unmistakably retro cartoon.
The model isn’t picking a single canonical interpretation of “retro cartoon” and printing it four times; it’s exploring inside that style space.

The same thing works across radically different modes.
Switch the prompt to a cat riding a bicycle, dreamy cinematic scene at 16:9 and you get a whole spectrum of takes on that vibe — different lighting, different camera languages, different moods, all sitting comfortably under the same “dreamy cinematic” umbrella.

And if you want to push the model toward something less polished, you can.
Extremely grainy lo-fi VHS still gives you exactly that — low resolution, chromatic aberration, the kind of texture most models actively try to clean away.
This is where you can feel the unopinionated part of Krea 2 most clearly.
The model isn’t holding back, isn’t quietly steering you toward “tasteful,” isn’t softening the edges of the look you asked for.

Style references: dial the look up and down

Once you’ve found a look you like — whether it came out of one of these exploratory rounds or you brought it in from somewhere else — style references let you carry it forward into completely different prompts.
We spent as much time on the style transfer system as we did on the foundation model itself.

The way it works: you drag any image into the prompt box, into the area marked add as style transfer, and then you write whatever prompt you want.
Under the hood, the system extracts the stylistic components of that image — color, texture, composition cues, the painted-or-photographic feel of it — and applies them to your new generation.
So if you liked the painting style of one of those cat-on-bicycle outputs and want to see what it does with a completely different subject, you can.

The most important knob here is strength.
Strength controls how hard the style pushes against the base model.
At 50% you get a balanced blend — recognizably stylized, but the prompt is still firmly in charge.
The interesting part is what happens at the extremes.

Drop the slider to 20% and the same prompt with the same reference produces something much more realistic.
You can still see hints of the reference: a touch of the color palette, a faint painted quality.
But the base model has the upper hand and it pulls the image toward photography.
This is useful when you want a style to inform a generation rather than dominate it — when you want a whiff of the reference instead of the whole thing.

Push it the other way to 80% and the relationship inverts.
Now the reference is in charge.
You get a full painting in the same palette, the same brush strokes, the same compositional language as the reference image.
Push it even further and the model starts hunting for places to put the reference’s color — sometimes overriding the subject itself to make the style fit.

You can see this in the outputs where the model tries so hard to transfer the bike’s color into the horse that it starts painting parts of the horse itself in that color.
That kind of “breaking” is informative; it tells you exactly where the style transfer is trying to land.

The other thing you can do — and this is where style references really start to feel like a creative instrument — is combine them.
You can stack up to four references at once, each with its own strength slider.
Add a darker knight reference at 70% on top of an illustration at 50% and you start seeing the interesting part: stylistic components from both images coexisting in the same output.
The chrome and the darkness from the knight, the painted aberrations and the looser hand from the illustration.
The horse comes out partially chrome, partially painted, with backgrounds and lighting borrowed from both worlds.

Re-balance the same two — illustration to 75%, knight down to 57% — and the result tilts toward the illustration: more of the painted artifacts, only certain parts of the horse rendered in chrome instead of the whole thing.
You can literally feel each slider pulling on a different aspect of the output.

Add a third reference into the mix — a line illustration at 80% on top of the painting at 60% and the knight at 44% — and the whole process starts feeling less like prompting and more like turning physical knobs on a creative tool.
You don’t have to write any new text.
You can move sliders, swap references, raise one and drop another, and watch the output rearrange itself in response.

For us this is the most honest answer to the question “how do you give an AI tool real creative control”: you give the user variables that map to visual qualities and let them play.

Moodboards: a richer kind of reference

Style references are precise.
You hand the model a specific image, it extracts the style, you control how hard that style pushes.
Moodboards are the other new thing in Krea 2 and they work on a different axis. Two important differences:

• No four-image cap. You can throw as many images at a moodboard as you want. The whole point is that a moodboard is a set, not a single reference, and the system reasons over the set.
• The algorithm is doing more than style transfer. Moodboards use style transfer under the hood, yes, but on top of that they run custom LLMs and clustering across your images. They pick up on concepts, recurring characters, expressions, compositions, atmosphere — the actual mood of the set, not just its visual style.

The workflow is simple.
Open the sidebar in the image tool, click moodboards, create a new board, drop in a batch of images, and click analyze.
After a moment you get three columns back:

• Taste profile. A high-level description of the kinds of things the algorithms found in your moodboard. Useful both as a sanity check and as a kind of mirror — sometimes you see your own taste described back at you in a way you wouldn’t have written yourself.
• Keywords. The set of style tags the system will use under the hood every time you generate with this board.
• Avoids. Things the system will actively steer away from when you generate with this board. This is one of the more underrated bits — being able to encode what you don’t want is often more useful than being able to encode what you do.

Then you generate as usual.
Prompt a frog against a board of colorful illustration and you get frogs that pull the palette and the line work — and sometimes go further, picking up incidental details like little stars from the references and weaving them into the scene.

The output isn’t a “frog in the moodboard’s style” so much as “what would happen if a frog existed inside this universe.”
Sometimes that turns into the frog quietly watching its own bubbles like a confused tourist. That’s the point.

We’ve also shipped a set of presets so you can play with the system before you build your own.
Each preset is a hand-curated moodboard with its own taste profile, keywords, and avoids — you can swap them in and out and instantly see the same prompt rendered through completely different aesthetic universes.
Retro web is one of our favorites.

Apply it to the same frog prompt and you get pixelated, slightly chaotic 3D-collage territory — bits of late-90s web aesthetic colliding with rendered objects and stickers.
Sometimes the outputs lean realistic-with-a-vibe, like a collage that almost makes sense; sometimes they go fully pipe-and-3D-blob. Both are correct.

Expressive marker swings the same prompt into character territory.
The reference set is a bunch of expressive, slightly goofy illustrated characters, and the system keeps that mood consistent across whatever you generate with it.
The frog comes out looking a little funny, a little stylized, very obviously a character and not just an object in a style.

This is the part of moodboards that style references can’t quite do on their own: transferring not just look but attitude.

The mental model that’s worked best for us: where style references are about transferring a look with precision, moodboards are about handing the model a vibe and seeing what it does with it.

Try it

Krea 2 gives you a lot of room to explore and a lot of aesthetic control.
Exploration mode for figuring out what you want.
Style references for carrying a specific look across prompts and dialing it in with strength.
Moodboards for handing the model a whole creative universe and letting it generate inside that universe.

They’re designed to be used together — start with exploration, refine with style references, lock in an aesthetic universe with a moodboard — but each one stands on its own too.

The best way to feel the difference is to open the image tool and start pushing it.

Open the image tool
Try Krea 2, style references, and moodboards.

Original source

How it works

Krea 2 is built around style control: not just what should appear in an image, but how it should feel. Style references and moodboards already let you guide Krea 2 with visual examples. LoRA training takes that one step further.

Starting today, we’re rolling out Krea 2 LoRA training in beta — our most powerful fine-tuning system to date. Train Krea 2 on your own specific style, object, or character with precision, then use it directly in the Image tool.

Krea 2 LoRAs are available for Max and Business subscribers while we test in beta.

LoRAs aren’t new to Krea — we’ve supported them on Flux, Qwen, and Wan for a while. What’s new is the quality. Krea 2 LoRAs hold style, character, and material identity at a level we haven’t seen from any of the earlier backbones.

Three steps from a folder of images to a reusable Krea 2 LoRA.

1. Open the trainer

Head to /train, click Train new LoRA, and hit Next step.

2. Add images, pick the model, set steps

Drop in a set of images (at least three) that share the style, character, or object you want to capture.

On the right sidebar, choose Krea 2 Medium or Krea 2 Large — Large trains stronger, Medium trains faster. Adjust Steps if you want the LoRA to learn more aggressively; the default is tuned to work for most datasets.

Krea auto-captions your dataset before training. Captions tell the trainer what to learn and what to ignore, so a one-off background or prop doesn’t accidentally become part of the LoRA. You can edit captions before kicking off the run.

3. Use it in the Image tool

When training finishes, your LoRA appears in your Train library with preview images. Open it from there, or hit the LoRA button while generating in the Image tool with Krea 2 selected.

You can dial strength up or down, and combine multiple LoRAs — stack a character with a style, or layer two visual languages on top of each other.

When to reach for a LoRA

Style references are great when you want to guide a single generation. A LoRA is better when you want a visual direction to become reusable — a painterly look applied across subjects, a character placed into new scenes, a product or brand language you can keep generating from without rebuilding the direction every time.

Krea 2 LoRAs are especially useful when the thing you care about isn’t easily described in a prompt: a texture, a recurring face, a brand object, a sketch style, a lighting habit, a strange material.

Made with a Krea 2 LoRA

beccu.studio
@beccu.studio
“A custom creature LoRA trained on Krea 2 — same identity across wildly different scenes and moods.”

A few tips

Use a focused dataset.
For a style, keep images visually consistent but varied enough that the model learns the style instead of memorizing one composition. For a character, include different angles, expressions, lighting, and backgrounds.

Captions matter.
If an image has a detail you don’t want the LoRA to learn, call it out in the caption. Auto-captions are a good start; a quick manual pass usually makes the LoRA noticeably better.

Start with the defaults.
Krea shows the estimated compute before you submit, and the default Steps count works for most datasets. Bump it up only when you want the LoRA to learn more strongly.

Keep your first LoRA narrow.
One clean character, one style, or one product identity beats trying to teach everything at once.

Private by default

Trained LoRAs are private when created. Keep them to yourself, share with collaborators, or make them discoverable later. If you make a style public, other Krea users can generate with it — but your original training images stay private.

Train a Krea 2 LoRA

Upload a set of images and turn a style or character into a reusable Krea 2 model.

Start training

Frequently asked questions

Original source

By the Krea Team. Last updated May 2026.

Mood boards vs. style references

Mood boards are one of the new tools that ship with Krea 2, and honestly — they’re our favorite.

A quick refresher on style references: you pick up to four images, and the model transfers their style onto whatever you prompt. It’s focused, surgical, and gives you a lot of control over how that transfer happens.

Mood boards are a different animal.

Two big differences:

• More than four images. You can pile in as many as you want.
• A more complex system underneath. Mood boards sometimes use style references behind the scenes, but they also run custom LLMs and clustering methods to read everything about the images you upload — not just style. Concepts, expressions, characters, the overall vibe — it all gets factored in.

The result: a tool that goes further than style transfer. It pulls the whole world of your reference set into every generation.

How to use mood boards

Open the sidebar in Krea — Mood Boards is the second item. Click in, hit create new mood board, drag and drop your images.

Before you can generate with it, you need to analyze the board. That’s the step where all those algorithms run and Krea builds a profile of your references.

Once analysis is done, you get three columns:

• Taste profile — a high-level description of what the system found in your board.
• Keywords — style tags that get applied under the hood every time you generate with this board.
• Avoids — things the system will actively steer away from.

Hit generate mood board to drop back into the image tool with the board selected. Now anything you prompt will be filtered through that whole aesthetic.

What it actually does

Prompt something simple — say, “a frog” — and you’ll see the mood board doing more than copying colors. If your references have stars floating around, your frog might end up in a starry scene. If the expressions in your references are goofy, your frog comes out looking a little dummy too.

That’s the whole idea. Style references transfer style. Mood boards transfer everything — concepts, ideas, palette, mood — and generate with all of it at once.

Sometimes it locks onto one dominant style. Sometimes it blends. And sometimes it pushes into something a little crazier that still belongs to the world of your references. That last part is what makes it so good for exploration.

One prompt, three mood boards

Same prompt — “a frog” — generated through three different boards. Same subject, completely different worlds.

Presets

Krea ships with a bunch of curated mood board presets. A few to try:

• Retro web — pixelated UI components, low-res 3D vibes, collage-y aesthetics.
• Expressive marker — hand-drawn characters with funny, loose energy.
• Film noir — photographic, cinematic, a little grainy.

Same prompt, different preset, completely different output. It’s the fastest way to feel how much a mood board changes a generation.

Why we love it

Mood boards give you aesthetic control without locking you into a single look. They leave room for the model to surprise you — within the world you defined. For anyone who likes to explore visually, it’s easily one of the most powerful tools in Krea 2.

Try mood boards in Krea 2

Build your own board, analyze it, and generate.

Original source

By the Krea Team. Published May 12, 2026.

This is Krea 2, our first foundation model built completely from scratch and focused on aesthetics and creative control. When creating an image with AI, there are two main pieces that you need to define: what do you want in that image, and how do you want that image to look?

Most image models are great at the first part. They can handle really complex prompts with no problem. But when it comes to style, they often want to give you something that looks good. Something polished, safe, and nice. Nothing too crazy. We have talked about the AI look in the past, and about the barriers it creates when you try to get expressive or artistic styles out of these models.

So for Krea 2, our focus has been on how you want the image to look. We wanted something capable of rendering pretty much any style: from the grainiest film photography to the cleanest studio shot, cinematic stills, different kinds of illustrations, complex digital paintings, and any kind of experimental direction.

To get there, we put as much effort into building a style transfer system as we put into creating the foundation model itself. You can pass an image into this system, and Krea 2 will understand its style components and transfer them into the output. It also lets you control how much the style should influence the final image, and it lets you combine multiple styles together.

This is one of the main ideas behind Krea 2: style should not be a vague prompt word. It should be something you can guide, mix, strengthen, reduce, and push. In the image tool, you can use style references to shape the output directly. You can add multiple references, combine them, and adjust how strongly they influence the image.

If you want the model to stay closer to a reference, you can do that. If you want the reference to be a lighter direction rather than the whole image, you can do that too. The model also includes controls for how much variation you want across a batch. You can keep a set of images more cohesive, or push it toward a wider spread of palettes, details, and style choices.

The goal is not just to generate a good image. The goal is to give you room to explore a visual direction. If there is one thing we want to do at Krea, it is to build creative tools. The kinds of products and features that we have been able to build up until now have always been limited by the kinds of models we had access to.

With the start of this research lab, we expect to create technology that allows us to build creative tools that treat AI as an actual creative medium. Something that feels raw, flexible, unopinionated, and unconstrained. Something that you can break if you want to. Something that does not limit the types of visuals you can create with it.

We cannot wait to see what you do with Krea 2, and we are getting ready to ship many new updates and features over the following weeks.

Try Krea 2

Generate images with our most expressive model yet.

Original source

By the Krea Team. Published April 2, 2026.

Seedance 2.0 is available on Krea. It’s the strongest AI video model we’ve tested for motion coherence, camera control, and clip-level stability.

Seedance 2.0 is now available on all paid plans. Try it in the video tool.

What it does

Full-clip coherence. Lighting, textures, and spatial relationships hold from first frame to last. No mid-shot drift, no warping.

Camera pans keep direction. Tracking shots maintain depth. A slow reveal looks intentional, not approximated.

Characters stay recognizable throughout the clip. Faces, clothing, proportions persist across time instead of getting rebuilt frame to frame.

The output is stable enough to edit, composite, and drop into production pipelines. Close-ups and macro shots hold up under scrutiny.

How to try it

Open the video tool, pick Seedance 2.0 from the model selector, write your prompt, and generate. Same workflow you already know.

Availability

Seedance 2.0 is available on all paid plans. Pick any paid tier and start generating. Check out our plans.

Try Seedance 2.0

Best-in-class motion coherence and camera control.

Original source

By the Krea Team. Published March 26, 2026.

Krea Edit now supports annotations

Mark up multiple regions of an image, write a separate prompt for each one, and generate all the changes in a single pass.

Editing an image region by region used to mean working through them sequentially. Select an area, describe the change, generate, wait for the result, then move to the next one. Five things to fix meant five separate rounds.

With annotations, you mark up everything first, then generate once. Draw rectangles around every area that needs work, write what you want for each one, and the model processes all regions together.

How it works

Open an image in Krea Edit and start drawing rectangles on the canvas. Each region gets a numbered badge in its own color so you can tell them apart. A card appears anchored below each rectangle where you type your prompt.

You can describe something completely different for each region. Swap a background in one, change an outfit in another, add an object somewhere else. Each prompt is independent.

Annotations can also carry reference images. If you want a region to match a particular look, drop the reference right into that region’s card. Upload from your files or pick from your existing assets. The model uses it as a visual guide for that area only.

The sidebar lists every annotation with its color badge and prompt text. Click any entry to jump to that region on the canvas.

One pass

When you generate, the model handles each prompt on its own while keeping untouched areas intact. One generation, all your edits.

For single changes, the brush and selection tools work the same as before. Annotations are for when you look at an image and see three or four things to fix at once.

Try Annotations

Edit multiple regions in a single generation.

Original source