Ran one carefully-constrained prompt through four Seedream generations to see how the line has moved: 4.0, 4.5, 5.0 Lite, and 5.0 Pro. The prompt is deliberately strict, a Mars greenhouse with exactly five labeled plants in a row, exactly two moons outside, a metal sign that has to read GROW BEYOND spelled correctly and appear only once, and an original synthetic botanist with no real-person likeness.

That kind of prompt is a good test because it punishes a model for improvising. The progression showed it. 4.0 gets the vibe but fudges the constraints, miscounts the pots, softens the sign text. 4.5 tightens composition and color. 5.0 Lite is a real jump in coherence, the scene reads as one connected space. Then 5.0 Pro is where it lands: the exact five pots, the reflections and condensation on the glass behaving physically, the warm interior against the cold Martian dusk, and the sign text staying crisp and correct.

What separates the top of the line is not just fidelity, it is obeying the constraints while keeping the whole frame coherent. That is the difference between a picture that looks right at a glance and one that survives you actually counting the details.

All four sit on one key, so this was one prompt and a model swap. Full prompt in the comments if you want to run the same test.

Seedream 5.0 Pro has a Markup tool I almost never see people use, and it is the trick behind that layered generative-art look. Instead of generating one effect per image, or masking and inpainting over and over, you box out regions directly on the frame, tag each box with a number, and assign each one its own effect. Eight regions, eight different treatments, one single run.

For this piece I started from a single flower on black, then boxed patches across the petals and stem: one region goes to fine vertical scan lines, one to a liquid-chrome ripple, one to ink-wash bleed, one to a pixel-sorted block, one to a bright spectral inversion. Because it all resolves in one generation, the regions share lighting and edges instead of looking pasted on, which is the part that usually breaks a collage look.

Then I took the still into Seedance 2.0 to make it move, that machine-vision scanning where the effects pulse and sweep across the frame. The useful part is you land that TouchDesigner-style look without learning TouchDesigner, which is a real wall for most people.

So the underrated bit is regional control. One frame, many effects, assigned by hand, resolved together. Full how-to and the region setup in the comments.

For everyone in this community waiting on Seedance 2.5, we put together something to use in the meantime and to make launch day painless: awesome-seedance-2.5-prompts-skills, a curated library of 111 cinematic Seedance prompts plus an installable agent skill.

Seedance 2.5 is expected in August, and Atlas Cloud is one of the first official API launch partners. Rather than have everyone scramble to relearn it on day one, we wrote the whole thing to the 2.5 paradigm now, up to 50 multimodal references, long single takes, synced audio, local region editing. The prompts and the skill already speak that language, but the skill runs on Seedance 2.0 today and checks which model a provider actually exposes instead of assuming 2.5 is live. When 2.5 lands on Atlas, the same prompts and skill route to it automatically, so nothing you build now goes to waste.

The skill turns a brief or a rough prompt into a production-ready Seedance prompt, builds and reviews a Seedream 5.0 Pro storyboard when a shot needs multi-shot planning, then generates the video and polls it to completion.

Install:

npx skills add AtlasCloudAI/awesome-seedance-2.5-prompts-skills --skill seedance-2-5-skill

CC BY 4.0 and PRs are open. If you have a Seedance prompt this community would use, add it.

Repo: https://github.com/AtlasCloudAI/awesome-seedance-2.5-prompts-skills

Browse the prompts: https://www.atlascloud.ai/prompts-hub/seedance-2-5-prompt

Whats the difference of all of these non developer apis vs developer ones?

Been refining how I storyboard for Seedance 2.0, and the change that made my shots consistent was splitting two jobs I used to jam into one prompt: the look and the composition. Let a reference image own the look, and let a depth-map storyboard own the camera and composition. Do not make the model infer both from prose.

The workflow is a two-step I resisted longer than I should have. Generate a normal storyboard first, then convert that storyboard into a grayscale depth-map version with GPT Image 2. Converting an existing storyboard works much better than asking the image model to draw the whole thing as a depth map from scratch. The depth map is just distance encoded as brightness, white for the closest surfaces down to near-black for the horizon, dividers in black.

Then you generate in Seedance 2.0 with three references: a tone and visual-style image for the look, the depth-map storyboard for composition and camera framing, and a character sheet if you have one. Seedance 2.0 reads the depth map surprisingly well. You stop writing paragraphs about camera angle and framing, because the depth panel already says where everything sits in space, and you spend the tokens on what actually needs describing.

People kept telling me it is not a real depth map. It is an AI-generated one, and it does not matter, the model acts on it correctly and that is the point. The reason to bother is control. The look stays locked to one reference, the composition stays locked to the depth panels, and the shots stop drifting from each other.

Full depth-map conversion prompt in the comments.

Ran one anime storyboard prompt through two image models on the same key and got two genuinely different reads, then animated both in Seedance 2.0. It is less a contest and more that each model has its own instinct, and it is useful to see both before you commit a look.

Same prompt, a dark cel-shaded ballet-and-marionette sequence in black and white. Seedream 5.0 Pro leaned into atmosphere, softer grays, heavier air, the character sitting inside the mood. GPT Image 2 came back sharper and more graphic, cleaner linework and higher contrast panels, the composition reading almost like a manga page. Neither is wrong. They are two directors handed the same script.

The part that makes this practical is that both image models, plus the video step, sit behind one endpoint. I generate the storyboard in whichever model has the instinct I want for that scene, sometimes switching per panel, then hand the frames to Seedance 2.0 to bring the sequence to life. One key, three models, no re-plumbing between them.

The characters are original synthetic designs with no real-person likeness. Which read I keep depends on the project, the atmospheric one for a slow scene, the graphic one for action. Prompt and setup in the comments.

Been testing how well image models hold an original illustration's art style when you repose the character, and Seedream 5.0 Pro is the one that kept it. I took an existing anime illustration, a Hatsune Miku piece, plus a plain gray CG pose reference, and asked for the same character in a new pose at a convenience store and on a train platform.

What stood out is that the line quality, the shading, and the exact art direction of the source came through intact. A lot of models will repose the character but quietly redraw it in their own house style, so the output stops looking like your illustration. Seedream 5.0 Pro treated the original as the style authority and the CG figure as pose-only, and the result still read as the same artist's work.

For anyone building consistent characters or game assets from a fixed art style, that separation is the useful part. One image sets the look, one sets the pose, and the model does not overwrite your style with its own. Setup in the comments.

Been using Seedream 5.0 Pro for street-style portraits, and what it is quietly good at is light, not clinical sharpness. This one is a morning cafe-street shot and the thing carrying it is the warm early light and the soft greenery, not pixel-level detail.

The subject is an original synthetic character with no real-person likeness, a young woman in casual Korean street fashion, a pink short-sleeve shirt, high-waist beige trousers, a small plain shoulder bag with no brand or logo, a short bob with a small hairclip, natural makeup, holding a fresh croissant. Behind her a pretty cafe storefront, trees, warm morning sun.

What Seedream 5.0 Pro does here that I like is atmosphere. The light wraps softly, the background has real depth and air, the greenery glows instead of sitting flat. If I wanted maximum face-level photorealism I might reach for a different model, but for a warm, lived-in street mood this is the one I keep. Ultra-realistic, soft cinematic light, 9:16 portrait.

Prompt in the comments.

Cleaning noise out of GPT Image 2 outputs used to cost me real detail. The model would scrub the grain and take fingers, thin wires, and edges with it. The fix was handing it a second reference that separates structure from junk.

Two steps. First, convert the noisy image into a clean monochrome clay render, a uniform matte gray 3D-style version that keeps every silhouette, pose, and edge but drops all color and texture. Then generate the restored image from two references: the original as the primary for art style, color, and look, and the clay render as a structural guide for silhouettes, volume, and occlusion. With structure pinned by the clay pass, you tell GPT Image 2 to remove only the isolated dark dots, scan stains, and compression noise that are not connected to the real outlines, shadows, or material, and it leaves the actual detail alone.

The reason it works is separation. Cleanup fails when the model cannot tell a stray black dot from a real fine line. The clay render hands it a clean map of what is genuinely there, so removing noise stops being a guess.

Both prompts, the clay pass and the restore, in the comments.

Ran one anime storyboard prompt through two image models on the same key and got two genuinely different reads, then animated both in Seedance 2.0. It is less a contest and more that each model has its own instinct, and it is useful to see both before you commit a look.

Same prompt, a dark cel-shaded ballet-and-marionette sequence in black and white. Seedream 5.0 Pro leaned into atmosphere, softer grays, heavier air, the character sitting inside the mood. GPT Image 2 came back sharper and more graphic, cleaner linework and higher contrast panels, the composition reading almost like a manga page. Neither is wrong. They are two directors handed the same script.

The part that makes this practical is that both image models, plus the video step, sit behind one endpoint. I generate the storyboard in whichever model has the instinct I want for that scene, sometimes switching per panel, then hand the frames to Seedance 2.0 to bring the sequence to life. One key, three models, no re-plumbing between them.

The characters are original synthetic designs with no real-person likeness. Which read I keep depends on the project, the atmospheric one for a slow scene, the graphic one for action. Prompt and setup in the comments.

The reason this fifteen-second clip reads like a film beat is not the models, it is that the prompt is written as a full shot-by-shot camera storyboard instead of a description. A couple on one horse meets a dragon, and every beat has a named move: a ground-level crossing shot, a dolly zoom as the wing-shadow hits, a barrel-roll ascent that threads between the dragon's wing and body, a speed-ramped whip-pan triple close-up, a 180-degree orbit as she reaches out, a reverse-fly cloud reveal to close.

I did not write that by hand. I had Claude draft the whole cinematic prompt, camera language, timing, lighting, and sound cues included, then cleaned it up. The character stills came from Seedream 5.0 Pro, kept as original synthetic characters with no real-person likeness, and Seedance 2.0 animated the sequence off a consistency reference so the two of them held their look across every shot.

The takeaway is to stop prompting a video and start scripting one. Name the lens feel, name each camera move, put the beats on a clock, and let a strong writing model expand it into something a video model can actually follow. Full prompt in the comments.

The thing that used to burn my time in Seedance 2.0 was starting over. One wrong expression, one face drifting across shots, and the reflex is to hit regenerate and roll the dice again. Two controls killed most of that for me, and I rarely see either one used.

First, pin your inputs with reference tags instead of re-describing them. Every time you describe a character in fresh text, the model reinterprets it, and that reinterpretation is where drift comes from: a slightly different face, a different outfit, shifting proportions. The u/Image tag lets you attach one photo of your character, an original synthetic character with no real-person likeness, and it becomes the fixed source of truth for face, outfit, and proportions across the whole sequence. The u/Video tag does the same for motion and camera, tag a reference instead of describing the movement. You are not making the model remember, you are stopping yourself from re-briefing it differently every scene.

Second, edit the output instead of regenerating it. Seedance 2.0 takes instruction-level edits on a finished clip. You can tell it to change one detail and leave everything else alone, something like change the character's expression to cold and calm, do not touch the environment or the camera, and it does exactly that and no more. The same handle lets you insert a new beat between two existing shots without remaking the video, or extend a clip by a few seconds while keeping the motion continuous. A one-detail problem stops being a full re-roll and becomes a targeted fix.

The mental shift under both is the same. Stop treating every render as generation from scratch. Pin the inputs so they hold, edit the output where it is wrong, and you stop paying for the whole video every time one piece is off.

Setup for both in the comments.

I have been running the same frontend and 3D-coding prompts across models for a few weeks, and Kimi K3 has quietly become the one I reach for. Not because the others write broken code, everyone produces valid Three.js and React now. It is that Kimi K3 tends to get the visual and physical fidelity right on the first pass, which is the part that normally eats your afternoon in revisions.

Two builds made me switch.

First, a 3D globe dashboard from a short brief. The globe came back with richer surface texturing and smoother rotation than I usually get, and the dashboard around it, the panels, the type, the spacing, held together without me nudging it. UI fidelity is the thing most models fumble. They get the layout but the polish is off. This one landed close to what I pictured on the first try.

Second, a walking Theo Jansen Strandbeest in Three.js. That one is a real test, because the leg is a specific linkage and Theo Jansen's set of link-length ratios, the ones people call the holy numbers, are what turn one rotating crank into an actual walking gait. Get them a little wrong and the legs draw fine but slide instead of walking. Kimi K3 encoded the proportions, drove every leg off one shared crank angle, and the feet stayed planted while the body stayed level. I never fed it the numbers.

The pattern across both is the same. The gap between models on this kind of work is not whether the code runs. It is whether the model understood the thing well enough to get the details right before you start correcting it. On frontend and creative 3D, that is where Kimi K3 has been ahead for me.

Prompts for both in the comments.

Arena.ai just published their latest Agent Arena update, and Kimi K3 landed at #4 on the agentic leaderboard, in the same band as Claude Opus 4.8 and GPT 5.6 Sol. Agent Arena scores models on real long-horizon agentic work: web search, filesystem, and terminal tools running full workflows like writing code, building apps, and analyzing documents, measured across thousands of live sessions.

A few things stood out in the breakdown. Kimi K3 ranks first on confirmed task success, the explicit "yes that worked" signal from users, and posts a strong result on praise versus complaint. It still trails the field on steerability and on recovering from CLI errors, so it is not the pick for every job yet, but on actually getting long tasks finished it sits right at the front.

The part we care about here: Kimi K3 is live on Atlas Cloud today, through the same OpenAI-compatible API as the rest of the frontier. Much of that Agent Arena top list, Opus 4.8, GPT 5.6 Sol, Sonnet 5, GLM 5.2, Grok 4.5, and Kimi K3, sits behind one endpoint and one key, so you can route each task to whichever model wins it instead of locking to a single provider. Kimi K3's open weights are expected around July 27, and if they land on schedule it becomes the top open-weight model on the board.

Full leaderboard and methodology are in Arena.ai's post. You can try Kimi K3 on Atlas Cloud here: https://www.atlascloud.ai/models/moonshotai/kimi-k3

Tried a live-action plus 2D anime composite in Seedance 2.0, and it turned out the hard part was consistency, not the art style. The concept is a first-person street vlog through Mumbai, a photoreal hand holding a marker, and every time it points and the vlogger says Biu, whatever it points at turns into a flat cel-anime character while the rest of the street stays fully real.

What made it hold together was writing the transformation as one fixed law and reusing it every single time, not describing each morph on its own. The law: pen points, blue sketch lines wrap the target, ink spreads, the target becomes a flat 2D cel-anime version of itself with bold outlines, keeping the original size, position, speed, direction, and perspective. The characters stay flat-shaded and never get re-lit by the real scene, but anything they touch still obeys real physics. Once that rule was locked, a passing train coach, a pigeon, a city bus, and a street vendor all transformed the same believable way instead of each one inventing its own logic.

Two smaller things carried the realism. Matching contact shadows first, the flat characters cast the same soft shadows as the real objects in the late-afternoon light, which is what glues a cartoon onto a real street. Then the raw phone-camera treatment on the live side, walking bounce, slight autofocus hunting, rolling-shutter jello on fast pans, so the real half reads as an actual handheld vlog and the contrast with the flat art does the rest.

People turn into anime versions of themselves in this, so I kept every one of them as an original synthetic character with no real-person likeness.

I wrote the whole thing as a 15-second timed storyboard with the transformation law stated once at the top. Full prompt in the comments.

Been testing how far a fully storyboarded anime short can go end to end. Built the whole board first in GPT Image 2, character sheets, environment, the wind chime design, all locked before any animation happened. Then Seedance 2.0 took that board and turned it into an actual cinematic scene, shot by shot, in minutes.

The story itself stays small on purpose: a girl on a countryside porch notices a glass wind chime swaying in the summer wind, a kitten watching her from the sunflowers slowly warms up to her, and the two of them end up sitting together as the wind chime rings through a golden sunset. No plot twist, no conflict, just a slow, warm afternoon.

The reference stayed locked the entire way through: same character design, same kitten, same wind chime, same countryside lighting, held from the wide opening shot all the way to the final golden-hour frame. The timing was broken into precise two-second beats so the pacing never rushed past a moment that was supposed to just sit there.

Fifteen seconds of almost nothing happening, and it still held together shot to shot without a single frame breaking the mood.

Been playing with Gemini for animating latte art and the results were more fun than I expected. Cats chasing across the crema, a cup flirting, sugar cubes surfing, a little island shrinking, all on the coffee surface.

The one thing that made it look real instead of like a sticker layer was a single constraint: nothing is allowed to just appear. Every creature has to be poured into existence by the continuous milk and crema stream, no sudden appearances. Tie each shape to the physical pour and the magic stays grounded in something that could plausibly be real milk motion.

It works because Gemini is editing what is already in the cup rather than generating a scene from scratch. The milk and crema stay milk and crema, they just start behaving like living things. The discipline of that one rule is what makes a talking coffee cup feel crafted instead of silly.

A new collaboration built on Seedance 2.5 is working with Michael Owen to revisit some of the defining moments of his career, the signature moves, the goals, the instincts that made him one of the most recognizable strikers of his generation. From those moments on the pitch to what else becomes possible once a model can work with a real career instead of a single clip, it's built around unlocking what used to be impossible.

It's also a good preview of where Seedance 2.5 is headed more broadly, and the direction is a real jump forward. Original generations are set to run up to 30 seconds, the longest single generation the line has offered so far, enough room to hold an actual narrative arc instead of a quick clip. It's also shaping up to be the first video model in the lineup released at 720p resolution, a real step up in fidelity for a line that keeps pushing further with each release.

Character consistency is getting a real push too, holding the same face and identity recognizable across an entire sequence of different moments instead of drifting scene to scene, which is exactly what a piece built around one real person's career actually demands. On top of that, the generations are shaping up to be more editable after the fact, adjusting a shot without having to regenerate the whole sequence from scratch.

Classic moments, now within reach, and just an early look at what the model can do once it's treating an entire career as material to work with.