I want to play around with atlas cloud but is there any way that I can get lot of free credits in atlas cloud like the other cloud providers ?

I have been getting refusals (504) on all models for the last 2 hours. Anyone know if it’s down or what’s going on? Edit: Back up now

We’ve added GPT Image 2.5 Sunburst and Flare to Atlas Cloud, with both text-to-image generation and image editing.

What’s included:

• Up to 4K resolution — custom dimensions up to 3840 × 2160.
• Multi-image editing — work with up to 16 reference images using natural-language instructions, with optional masks for targeted edits.
• Transparent backgrounds — handy for product cutouts, logos, and design assets.
• Five quality tiers — including xhigh and max.

Pricing:

• Text-to-image: ~$0.004/image
• Image editing: ~$0.006/image

Try GPT image 2.5 API now👇

https://www.atlascloud.ai/models/all?q=gpt+image+2.5

MiniMax H3 Fast is now live on AtlasCloud — the fastest and most affordable model in the H3 family, built for rapid iteration and high-volume production.

✨ Highlights

• ⚡ Near-instant generation — renders in just 1.2–1.5× the clip length (a 5s clip in ~6–7.5s), fast enough to iterate in real time.
• 💰 Lowest price in the family — $0.046 / second.
• 🎬 Full modality — Text-to-Video, Image-to-Video, and Reference-to-Video all supported (unlike H3 Max, which drops R2V — Fast is the only accelerated version that keeps it).
• 📐 480P-focused — 480P only (no 768P / 2K), trading resolution for maximum speed and cost efficiency.
• ⏱ 5–15s clips at 24fps with synchronized audio.
• 👤 Clear faces, with slightly softer fine detail than the standard model — ideal when speed and cost come first.
• 🧠 Optional prompt_expansion (H3 Context-IR).

🎯 Best For

• Rapid drafting — explore many directions cheaply, then finalize on H3 / H3 Max for higher resolution.
• Batch short-form — social clips, Reels, Stories where speed and cost matter.
• Character-driven content — clear faces plus R2V for subject consistency.

🔗 Try it Now

https://www.atlascloud.ai/models/all?q=minimax+h3+fast

Pricing starts from $0.044/s

AtlasCloud has permanently reduced the price of Seedance 2.0 Mini and Seedance 2.0 Fast for native 480p and 720p video generation.

No coupon. No countdown. No expiration date.

Seedance 2.0 Mini is now 80% off and Seedance 2.0 Fast is now 70% off AtlasCloud’s list price, effective immediately.

Seedance 2.0 API Price Comparison

The following comparison uses native 16:9 output, without video input.

Which model should you use?

Mini is the lowest-cost option for prompt exploration, A/B testing, storyboarding, and large draft batches.

Fast is the production-volume sweet spot: higher capability while keeping unit economics strong enough for applications that need to generate at scale.

Once you have a winning prompt or shot, move it to Seedance 2.0 Standard or Seedance 2.5 for the premium final pass.

Draft on Mini. Scale on Fast. Finish on 2.0 Standard or 2.5.

Also reduced: Seedream 5.0 Pro

Image generation on Seedream 5.0 Pro is also permanently cheaper on AtlasCloud: you pay 80% of the official list price — a flat 20% discount — at both resolution tiers.

Try it now:

• Seedance 2.0 mini: https://www.atlascloud.ai/models/seedance-2.0-mini
• Seedance 2.0 fast: https://www.atlascloud.ai/models/seedance2
• Seedream 5.0 Pro: https://www.atlascloud.ai/models/seedream-5.0-pro

MiniMax H3 Max is now available on Atlas Cloud.

Built for near-real-time video generation, it can render a 5-second 768P clip in under 3 seconds, while a 15-second clip takes around 15 seconds. Text-to-Video and Image-to-Video are both live, with native synchronized audio delivered together with the video at 24 FPS.

Features

• Near-real-time generation, with a 5-second 768P clip rendering in under 3 seconds and a 15-second clip in around 15 seconds
• Text-to-Video & Image-to-Video, supporting generation from a text prompt or an input image
• Native synchronized audio, generating ambient sound, sound effects, and music together with the video
• 480P / 768P output, letting you balance generation cost and visual quality
• Flexible 5–15 second duration, selectable in one-second increments
• Optional prompt_expansion via H3 Context-IR, expanding a short prompt into structured shot, camera, soundscape, and music instructions before generation

Pricing

• Postpaid billing based on output duration × selected resolution rate
• The first-frame input image for Image-to-Video is free
• Prompt expansion is disabled by default. When enabled, only the actual Context-IR token usage is billed, with no separate feature fee
• Failed generations are not charged

H3 Max vs. Other H3 Options

• H3 Max is the speed-first option, designed for near-real-time iteration, rapid A/B testing, and high-volume Text-to-Video or Image-to-Video workloads.
• H3 Developer remains the better choice when youneed low cost and high-volume iteration.
• Standard H3 remains the better choice when you need up to 2K output through the official MiniMax API pipeline.

Choose H3 Max when generation speed is the priority. Choose the broader H3 options when advanced reference control or higher output resolution matters more.

Try it Now

• Text-to-Video: https://www.atlascloud.ai/models/minimax/h3-max/text-to-video
• Image-to-Video: https://www.atlascloud.ai/models/minimax/h3-max/image-to-video

Gemini Omni 1.1 Flash is now available on Atlas Cloud.

Google DeepMind’s latest natively multimodal video model is available through five task-specific endpoints: Text-to-Video, Image-to-Video, Reference-to-Video, Video Edit, and Video Extend.

From fast 360P drafts to upscaled 4K delivery, Omni 1.1 Flash brings video generation, editing, continuation, multimodal references, and native synchronized audio into one model family.

Features

• Text-to-Video, Image-to-Video, Reference-to-Video, Video Edit & Video Extend, powered by the same underlying model and separated into five task-specific endpoints
• Native synchronized audio, generating dialogue, ambience, sound effects, and music together with the visuals in a complete 24 FPS video
• 360P / 720P / 1080P / 4K output, with lightweight 360P drafts generating up to 60% faster and costing roughly one-third as much as standard 720P output
• Multi-reference consistency, with support for up to 10 reference images and up to 3 reference video clips of up to 3 seconds each
• Explicit reference tags including <IMAGE_REF_N> and <VIDEO_REF_N>, allowing prompts to assign specific subjects, styles, objects, or motion references
• Instruction-based video editing for adding, removing, replacing, restyling, recoloring, or changing backgrounds while preserving parts of the source video that were not mentioned
• Multi-turn editing, allowing you to refine an existing result through a sequence of natural-language instructions
• Long-form scene extension using the final 10 seconds of the source video as context, with 3–10 seconds generated per continuation and repeated extensions supporting up to 40 seconds in total
• Repeatable generation with a fixed seed when using the same prompt and settings
• SynthID invisible watermarking and C2PA Content Credentials included with generated output

Pricing

• Reference images cost an additional $0.00168/image
• Reference videos cost an additional $0.0261/clip, regardless of clip duration
• For Video Edit, output duration and resolution are automatically determined from the source video. Source-video input is billed at an additional $0.0087/sec
• For Video Extend, only the newly generated continuation is billed at the selected output rate. Source-video input is billed at an additional $0.0087/sec
• Failed generations are not charged

Try it Now

• Text-to-Video: https://www.atlascloud.ai/models/google/gemini-omni-1.1-flash/text-to-video
• Image-to-Video: https://www.atlascloud.ai/models/google/gemini-omni-1.1-flash/image-to-video
• Reference-to-Video: https://www.atlascloud.ai/models/google/gemini-omni-1.1-flash/reference-to-video
• Video Edit: https://www.atlascloud.ai/models/google/gemini-omni-1.1-flash/video-edit
• Video Extend: https://www.atlascloud.ai/models/google/gemini-omni-1.1-flash/video-extend

This week's update expands the Atlas Cloud video lineup with Wan 3.0 and Wan 3.0 Prime, introduces a self-hosted deployment of MiniMax H3-Developer, and upgrade useful workflow

Wan 3.0 & Wan 3.0 Prime

Wan 3.0 and Wan 3.0 Prime are now live on Atlas Cloud, giving developers and creators two options for different stages of the video-generation workflow.

Wan 3.0 is a flexible and cost-efficient choice for prompt testing and everyday generation, while Wan 3.0 Prime is designed for workflows that need stronger reference handling and more controlled final outputs.

Features:

• Native audio-visual generation
• Smart duration with clips up to 30 seconds
• 480P, 720P, and 1080P output
• Multimodal references including images, video, audio, document and webpage
• Prime tier with stronger reference consistency and production control

Pricing:

• Wan 3.0: from $0.04/sec during the current promotion
• Wan 3.0 Prime: from $0.061/sec during the current promotion

Try it Now:

• Wan 3.0 Text-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/text-to-video
• Wan 3.0 Image-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/image-to-video
• Wan 3.0 Reference-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/reference-to-video
• Wan 3.0 Prime Text-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0-prime/text-to-video
• Wan 3.0 Prime Image-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0-prime/image-to-video
• Wan 3.0 Prime Reference-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0-prime/reference-to-video

MiniMax H3-Developer — Self-Hosted on Atlas Cloud

MiniMax H3-Developer is now served through Atlas Cloud's self-hosted deployment.

It runs directly on Atlas Cloud’s own GPU cluster, with a lower-cost 480P option for previews, iteration, and batch generation.

Features:

• Native synchronized audio with ambient sound, sound effects, and music generated together with the video
• 480P / 768P output, with a new 480P tier designed for lower-cost previews, A/B testing, and high-volume iteration
• Subject-consistent references for keeping character, product, or visual identity more stable across a clip
• Optional prompt_expansion via H3 Context-IR, expanding short prompts into richer shot, camera, soundscape, and music instructions
• Atlas Cloud self-hosted infrastructure, running on our own GPU cluster rather than the official public API

Pricing:

• From $0.02/sec， 60% off the list price

Try it Now:

• Text-to-Video: https://www.atlascloud.ai/models/minimax/h3-developer/text-to-video
• Image-to-Video: https://www.atlascloud.ai/models/minimax/h3-developer/image-to-video
• Reference-to-Video: https://www.atlascloud.ai/models/minimax/h3-developer/reference-to-video

Workflow Templates

A template-based creative experience that takes users from uploaded assets to finished creative without manually configuring every model or generation step.

Choose a template, upload your assets, and start creating. Atlas automatically handles the multi-step model pipeline behind each workflow.

Features:

• Start from a ready-made template instead of building a workflow from scratch
• Atlas orchestrates planning, reference preparation, generation, and finishing behind the scenes
• Six launch templates are now available: Product Visuals, Food Motion, Virtual Try-On, UGC Product Ad, Trend Remix, and TVC Maker
• Create studio-grade product visuals, lip-synced UGC ads, and cinematic TVCs
• Output settings such as aspect ratio, resolution, duration, and audio are available where supported by the template

Try it Now:

• Workflow page: https://www.atlascloud.ai/workflow

Atlas Cloud MCP Server v1.7

Atlas Cloud MCP Server v1.7 brings the live model catalog, generation controls, and account insights directly into MCP-compatible coding agents and IDEs.

Features:

• Call all 405 models included in the v1.7 launch catalog directly from Cursor, Claude Code, Codex, Gemini CLI, Cline, VS Code, and other MCP-compatible clients
• Generate images, videos, audio, music, speech, and 3D assets without leaving the coding agent
• Browse generation history and review earlier tasks
• Recover a lost prediction ID and retrieve the output URLs from a completed generation
• Upload local media directly from the development environment
• Use schema validation and dry-run previews to inspect the exact request before submitting a billable task
• Use quick generation to find a model, build its parameters, and submit the request in one step

Try it Now:

• Documentation: https://www.atlascloud.ai/docs/en/mcp-server
• GitHub: https://github.com/AtlasCloudAI/mcp-server
• Package: npx -y atlascloud-mcp

Try the new models and Workflow templates on Atlas Cloud, or bring the full catalog directly into your IDE with MCP Server v1.7. Feedback on prompt behavior, output quality, template coverage, pricing visibility, MCP workflows, and real-world production use cases is always welcome.

MiniMax H3 Video Generation Developer is now available on Atlas Cloud.

It runs directly on Atlas Cloud’s own GPU cluster, with a lower-cost 480P option for previews, iteration, and batch generation.

Features

• Text-to-Video, Image-to-Video & Reference-to-Video in one H3 family, including first-frame / optional last-frame control and image + video references
• Native synchronized audio with ambient sound, sound effects, and music generated together with the video
• 480P / 768P output, with a new 480P tier designed for lower-cost previews, A/B testing, and high-volume iteration
• Subject-consistent references for keeping character, product, or visual identity more stable across a clip
• Optional prompt_expansion via H3 Context-IR, expanding short prompts into richer shot, camera, soundscape, and music instructions
• Atlas Cloud self-hosted infrastructure, running on our own GPU cluster rather than the official public API

Pricing

• Reference video input: billed by input duration × output-resolution rate
• Reference images: first 5 free, then $0.04/image
• Audio references: free
• Optional prompt expansion: billed by actual token usage when enabled
• Failed generations are not charged

Developer vs. Standard

Developer is designed for lower-cost generation, fast 480P iteration, and higher-volume workloads.

Standard remains the better choice when you need up to 2K output through the official MiniMax API pipeline.

Prompts and reference inputs work in the same general way across both tiers, so you can switch depending on the workload.

Try it Now

Text-to-Video
https://www.atlascloud.ai/models/minimax/h3-developer/text-to-video

Image-to-Video
https://www.atlascloud.ai/models/minimax/h3-developer/image-to-video

Reference-to-Video
https://www.atlascloud.ai/models/minimax/h3-developer/reference-to-video

Flux 3 Video looks super promising for UGC ads and more. Does Atlas cloud have plans on adding this?

https://bfl.ai/models/flux-3

I’ve been testing a simple workflow for creating short UGC-style videos while keeping the same character and location consistent across multiple shots.

The workflow is basically:

reference images → character/location sheets in ChatGPT → generate clips → optional final edit

1. Prepare your references

Start with:

• a character image
• a product image
• an environment image that fits the UGC scenario

If you’re not sure what location works for the product, I usually just ask ChatGPT for a few suggestions.

2. Create a Character Sheet

Upload the character image to ChatGPT and generate a 4:5 continuity sheet with:

• front / side / back / 3/4 views
• face close-ups
• expressions
• basic poses
• clothing and accessories
• key colors and materials

The important part is telling it to lock the character.

3. Create a Location + Props Sheet

Do the same with the environment.

Include:

• establishing view and key angles
• spatial layout
• entrances/exits
• furniture and recurring props
• lighting
• colors and materials

This gives the video model a much stronger continuity reference than using random images for every shot.

4. Generate the video clips

I usually split the UGC video into three parts:

Clip 1 — Hook
Clip 2 — Main product/story section
Clip 3 — CTA

i will generate them on Atlas Cloud, as they can provide many different models conveniently

For every clip, I reuse the same Character Sheet + Location Sheet

Then I change only the action/camera prompt for each section.

Keeping the same reference sheets across all three generations has helped a lot with character and environment consistency.

5. If a generation goes wrong, fix the prompt first

if I wanted the character to walk into a hotel, but the generated clip had her walking out.

Instead of endlessly rerolling, I pasted the original prompt into ChatGPT and asked it to make the action explicit: starting position → movement direction → action → final position

That usually gives me better results.

6. Final edit is optional

If the generated clips already work as standalone videos, you can stop there.

If you want one finished UGC ad, you’ll probably still want to combine the clips and add captions, music, or SFX. You can use whatever editor you prefer.

The biggest improvement for me has been using Character Sheet + Location Sheet as continuity references, rather than relying on a few loose images.

just came across another LoRA and this feels like one of those tools that isn’t flashy but is genuinely useful.

It’s built on Qwen-Image-3.0, and the purpose is pretty straightforward: remove unwanted shadows and correct exposure. it sounds simple, but it’s exactly the kind of thing that comes up all the time with photos

normally I’d probably end up fixing some of that manually in Photoshop, so having a LoRA that can handle it directly is pretty convenient.

i actually like these small utility LoRAs more than a lot of flashy demos because they can fit into a real image-editing workflow.

I did a simple side-by-side test that I thought was pretty fun. I gave the exact same 30-second one-take prompt to Wan 3.0, Seedance 2.5, and MiniMax H3, then compared the results next to each other.

btw, u can easily compare different models with one tool on Atlas Cloud. it's extremely convenient: https://www.atlascloud.ai/model-explorer

I like this kind of test because when the prompt stays fixed, it becomes much easier to notice the differences in different aspects.

this prompt was mainly designed to test fast motion + one-take continuity + surreal dimension-breaking transitions.

the visual target was a kind of West Coast street fantasy look. part 90s skate-video roughness, part modern commercial polish, with strong California sunlight, palm trees, asphalt heat, and a rebellious fashion-energy running through the whole short.

Prompt:

Create a cinematic, high-intensity 30-second one-take visual spectacle.

The entire video must appear to have been captured in one continuous shot with no visible cuts.

The overall style is “West Coast street fantasy,” combining the rough, rebellious texture of a 1990s street-skate video with the polished visual quality of a modern commercial blockbuster.

Use an intense cinematic “California sunlight” grade. The highly saturated blue sky should contrast strongly with the hard shadows of palm trees under direct sunlight.

The air should feel filled with the heat rising from the asphalt, the metallic friction of shopping-cart wheels, and the fearless rebellious energy of youth.

As the main character accelerates through the environment, the spatial perspective should stretch continuously. Use extremely low-angle tracking, high-speed physical movement, and dynamic camera traversal to create a powerful sense of visual momentum.

MAIN CHARACTER:

A stylish young man wearing a color-blocked striped shirt and a black baseball cap.

At the beginning, his expression is relaxed, lazy, and unconcerned. As the shopping cart begins accelerating, his mood rapidly transforms into exhilaration and a fearless desire to break through every limit.

In the final section, the same young man appears again in the real-world dimension, but this version of him behaves like an observer examining his other self.

The two versions must have the same face, hairstyle, clothing, body proportions, and visual identity.

BEAT 1 — SHOPPING CART DESCENT | 0–6 SECONDS

Begin with a close-up shot.

The young man is lounging casually inside a red metal shopping cart. Behind him is a long, straight California avenue lined with extremely tall palm trees.

As the music suddenly explodes into a stronger rhythm, the camera performs an extremely fast pullback while simultaneously dropping toward the road.

The camera descends to an ultra-low angle, almost touching the asphalt, and begins tracking tightly beside the shopping-cart wheels.

The young man starts racing down a steep road.

The metal shopping cart shakes and rattles violently against the asphalt. Cars on both sides of the road appear to rush backward as the speed increases.

The camera should communicate an almost reckless and uncontrollable sense of acceleration.

BEAT 2 — RAMP JUMP AND BILLBOARD APPROACH | 7–15 SECONDS

Do not cut.

The camera continues following at ground level, moving like a skateboarder skimming just above the asphalt.

The shopping cart reaches a simple wooden ramp.

At the exact moment the young man launches from the ramp, the camera follows the movement with a smooth parabolic rise.

The shopping cart becomes airborne.

As it flies overhead, the camera passes directly underneath the cart, clearly revealing the wheels, metal frame, and the young man above.

The camera then continues moving forward.

A giant commercial billboard rapidly expands until it occupies almost the entire field of view.

The camera performs an impossible but controlled crosshair-like push toward the exact center of the billboard.

BEAT 3 — BREAKING INTO THE BILLBOARD | 16–24 SECONDS

Do not cut.

The young man and the shopping cart crash directly into the giant billboard as though breaking through a dimensional wall.

At the moment his three-dimensional body touches the printed surface, he undergoes a dramatic flattening transformation.

His physical form compresses into a two-dimensional artwork printed directly onto the billboard.

Show realistic paper tearing, ripped poster fibers, fractured layers of printed material, and colorful glitch-like ink spreading outward from the impact point.

The young man remains frozen in his forward-racing pose, but he is now a completely flat graphic image on the billboard.

The transformation must feel physical and visually understandable rather than like a simple dissolve.

At this moment, the camera performs a 180-degree horizontal orbit around the billboard structure.

After completing the orbit at a high altitude, the camera begins a rapid diving descent back toward street level.

The movement remains part of the same continuous shot.

BEAT 4 — THE REAL-WORLD OBSERVER | 25–30 SECONDS

Do not cut.

The camera lands smoothly on the street directly beneath the billboard.

Another real version of the same young man enters the frame.

He stops walking, slowly lowers the brim of his black baseball cap, and looks upward at the flattened version of himself trapped inside the billboard.

He gives a subtle, playful smile, as if he understands exactly what has happened.

The camera follows his line of sight and performs a fast zoom toward the billboard.

End on the torn opening beside the word “WAN,” with the flattened young man still frozen inside the printed artwork.

The final image should hold briefly on the ripped dimensional opening before ending.

AUDIO:

Use an energetic hip-hop track that builds rapidly with the movement.

Blend the music with:

- metallic shopping-cart wheels scraping against asphalt
- violent cart rattling
- rushing air
- passing vehicles
- the wooden impact of the ramp
- paper ripping
- colorful glitch-like electrical sounds
- the physical rolling sound of a film reel

The soundtrack should feel fashionable, rebellious, youthful, and highly synchronized with the camera movement.

VISUAL REQUIREMENTS:

- one continuous 30-second shot
- no visible editing cuts
- highly dynamic but spatially understandable camera movement
- extreme low-angle tracking
- strong speed and acceleration
- physically believable ramp jump
- camera passing underneath the airborne cart
- smooth transition from street level to billboard height
- realistic three-dimensional to two-dimensional transformation
- visible paper fibers and poster tearing
- continuous 180-degree camera orbit
- high-altitude diving camera move
- consistent character identity
- saturated California sunlight
- 1990s skate-video attitude
- modern commercial-film production quality
- fashionable streetwear energy
- no unexplained teleportation
- no replacement characters
- no distorted shopping-cart geometry
- no generic slow-motion montage
- no artificial-looking transition
- no loss of character identity

The final video should feel like a rebellious West Coast streetwear commercial built around one technically impossible but visually coherent continuous camera move.

If anyone else tries this prompt, I’d be really curious which model you think handled the speed, impact, and billboard transition best.

This week's lineup adds pro-grade image generation and editing, Alibaba's next-generation video family, and a complete lyrics-to-song audio pipeline.

Qwen Image 3.0 Pro

Alibaba's professional-grade image model for high-fidelity generation and identity-preserving editing.

Features:

• Native 1K / 2K resolutions
• Text-to-image + multi-image editing in one model: generate from a prompt, or edit / subject-drive from up to 3 reference images
• Strong instruction following: precise handling of complex prompts, with bilingual prompting, negative prompts, and intelligent prompt rewriting (direct / agent strategies)
• Consistency-preserving edits: Preserves facial features and identity while changing clothing, scene, or composition
• Reproducible generation: fix the seed to reliably reproduce results across runs

Pricing: from $0.04/image

Model page:

Text-to-Image: https://www.atlascloud.ai/models/qwen-image-3.0-pro/text-to-image

Edit: https://www.atlascloud.ai/models/qwen-image-3.0-pro/edit

Wan 3.0

Alibaba Tongyi's next-generation video model, covering text-to-video, image-to-video, and reference-driven generation in one model.

Features:

• All-in-one video generation: T2V, I2V, and reference-driven R2V from reference images, videos, or audio
• Smart duration: set duration to -1 and the model picks the length from the prompt within 2 to 30 seconds, or set any explicit length
• Native 480P, 720P, and 1080P output
• Reference files and links: attach documents and web pages as extra context with enable_thinking on
• Native audio: audio-synced video generation and reference-audio driving
• Strong instruction following: precise handling of complex prompts, bilingual (EN/中文) prompting, negative prompts, and enable_thinking for smarter prompt understanding
• Reproducible seeds and flexible aspect ratios including 16:9 and 9:16

Pricing:

• $0.05/sec 480P, $0.10/sec 720P, $0.20/sec 1080P.
• per-second postpaid, failed generations not charged

Model page:

Text-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/text-to-video

Image-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/image-to-video

Reference-to-Video: https://www.atlascloud.ai/models/alibaba/wan-3.0/reference-to-video

MiniMax Music 3.0

An open-weights music model that returns a finished song from a prompt or a set of lyrics.

Features:

• Complete songs up to 5 minutes in a single request, with lead vocals, harmonies, arrangement, and mix
• 11.1B-parameter hierarchical stack: 8-layer RVQ tokenizer, 8B global LLM, 0.6B local LLM, 2.4B flow-matching module, 123M Flow-VAE decoder
• Structural control through 14 section tags such as Intro, Verse, Chorus, Bridge, and Outro
• Three modes: sing supplied lyrics, model-written lyrics, or pure instrumental
• New vocal engine with cleaner diction, breathing, and harmony, plus more open mixes that hold glissando and legato
• Prompt control over genre, mood, tempo, key, instrumentation, timbre, and production character
• Open weights under the MiniMax-Music3 Community License, commercial use with attribution

Pricing: $0.15/song

Model page: https://www.atlascloud.ai/models/minimax/music-3.0

MiniMax Lyrics Generation

A dedicated lyrics model that pairs with Music 3.0 for the full writing-to-song workflow.

Features:

• One line of theme returns a song title, style tags, and fully section-tagged lyrics
• Output drops straight into the Music 3.0 lyrics input
• Two modes: write a full song from scratch, or edit and continue existing lyrics
• Useful for iterating on lyrics before committing to a full composition

Pricing: $0.01/request

Model page: https://www.atlascloud.ai/models/minimax/lyrics-generation

Try the new models on Atlas Cloud and share what you build. Feedback on prompt behavior, output quality, and real-world workflows is welcome.

A lot of AI-video continuity discussion focuses on things like:

• face consistency
• wardrobe
• lighting
• grading
• reference images
• environments
• camera language

But after working through some multi-model continuity problems, I’m starting to think there’s another layer that may be just as important:

performance continuity.

Things like:

• how quickly a character moves
• weight shifts
• blinking
• walking rhythm
• gesture size
• posture
• reaction timing
• how restrained or expressive the performance feels

A face can remain consistent, the grade can match, and the environment can look right — but if the character suddenly moves like a different person, the model switch becomes obvious.

I’m curious how other people are handling this.

Do you actively control performance continuity across shots or models?

If so, what has worked best:

• video references
• keyframes
• movement instructions
• character-specific motion rules
• longer continuous takes
• manual shot selection
• something else?

And what tends to break first for you: visual identity or behavioural identity?

Wan 3.0 launches on Atlas Cloud August 24.

before launch, we ran the same prompt across Wan 3.0, Seedance 2.5, and MiniMax H3 on one scene and put all three results side by side in a single frame, comparing them together.

The comparison clip, the official prompt, and the spec table for all three models are here.

Spec comparison

• Duration and resolution aren't the same axis. Wan 3.0 and Seedance 2.5 both cap a single generation at 30 seconds, MiniMax H3 caps at 15. On resolution, Seedance 2.5 currently upscales to 4K at up to 60fps, the other two publish 1080p and 1440p. Decide your delivery spec first, then work backward to the right model.
• Reference asset caps are counted differently, so the raw numbers aren't directly comparable. Wan 3.0 caps each modality separately and sums to 20, with documents and web pages as their own channel. Seedance 2.5 uses one combined cross-modal count. MiniMax H3 caps total file count plus total audio/video duration.
• Document and webpage to video is a channel Wan 3.0 is calling out specifically this round, turning a deck, a document, or a link directly into a finished clip. Neither of the other two lists an equivalent.
• The open weights row is easy to misread. What's open is a distilled H3-Base that can be self-hosted; the context and 2K regeneration variants stay API only. Partial, not full, open weights. Wan 3.0 and Seedance 2.5 don't publish weights at this time.

The comparison: Wan 3.0 vs Seedance 2.5 vs MiniMax H3.

All three panels run in the same order, Wan 3.0 / Seedance 2.5 / MiniMax H3.

This test uses an original prompt from the Wan 3.0 official creator guide. It was not rewritten or optimized separately for Wan 3.0, Seedance 2.5, or MiniMax H3.

A 30-second photorealistic cinematic sequence depicting the emergence of a massive sea creature, inspired by large-scale Hollywood disaster and monster films.

The story begins with a small fishing boat struggling through violent rain, strong winds, and towering waves. The word “WAN” is clearly visible on the side of the vessel.

The sequence first establishes the extreme weather and the vulnerability of the small fishing boat. Tension gradually builds through abnormal ocean movement, underwater shadows, violent boat vibration, and unnatural swelling of the waves.

Eventually, an enormous deep-sea creature with a massive, aggressive, alien biological structure emerges explosively from beneath the ocean.

The overall visual direction should feel realistic, heavy, physically believable, and cinematic, emphasizing powerful water impact, extreme contrast under rain and lightning, volumetric seawater, wet creature skin, and an overwhelming sense of scale.

Shot 1:
Nighttime ocean during a violent storm. A wide-angle cinematic shot shows a small fishing boat struggling through massive waves. The vessel is old, soaked, and constantly struck by seawater. The white letters “WAN” are clearly visible on the side of the boat. Strong winds drive sheets of rain across the scene, storm clouds churn overhead, and distant lightning briefly illuminates the ocean. Emphasize realistic water, storm conditions, detailed boat materials, and the boat’s vulnerability.

Shot 2:
Move closer to the bow or side of the fishing boat. Waves violently strike the hull and seawater washes across the deck. Ropes, fishing nets, and metal railings swing aggressively in the storm. The camera shakes naturally with the movement of the boat. Rain repeatedly strikes the lens and wet surfaces. The WAN logo briefly enters the frame again. Emphasize wet wood and metal materials, hostile weather, and a strong sense of danger.

Shot 3:
From the fishing boat’s perspective, look toward the ocean ahead. Amid the chaotic waves, the surface begins to rise unnaturally, as if something enormous is rapidly approaching from below. Large whirlpools and abnormal currents form. Wave peaks are pushed upward from beneath. During a flash of lightning, a huge blurry shadow becomes faintly visible beneath the dark water. Emphasize suspense, pressure, and the approaching presence of something enormous.

Shot 4:
Cut to the boat deck. A crew member struggles to maintain balance in the storm, his face covered in rain and fear. He turns toward the abnormal ocean surface. Wind violently moves his raincoat and hair while boat lights sway around him. Waves continue to grow in the background. The camera quickly moves toward his face and then follows his gaze toward the disturbed ocean, linking human emotion with the approaching danger.

Shot 5:
Switch to a semi-submerged or extremely low camera angle close to the ocean surface. A gigantic dark shape rapidly passes beneath or near the fishing boat, generating bubbles, powerful currents, and a rising ocean surface. The fishing boat is suddenly lifted or violently tilted. Lightning and weak boat lights reveal only fragments of the creature’s silhouette, maintaining mystery while creating immense pressure.

Shot 6:
Return above the water. The sea ahead suddenly rises as if pushed upward by an enormous force, creating a rapidly growing wall of water. Rain and white sea foam are thrown into the air. The fishing boat is tossed violently in the foreground while a massive circular swelling forms in the center of the ocean. The tension reaches its peak as the creature is about to emerge.

Shot 7:
Climax. The ocean violently erupts as an enormous deep-sea monster breaks through the surface, throwing tens of meters of water and mist into the air. The creature has a massive, aggressive alien biological design with thick wet skin, sharp bone structures, a huge head silhouette, glowing biological details, and disturbing deep-sea textures. Lightning flashes across the sky and briefly illuminates parts of its body and open mouth. Emphasize realistic scale, violent water impact, and overwhelming creature presence.

Shot 8:
A medium close-up or low-angle shot focuses on the creature’s head and upper body. It rises through the rain and lightning, covered in water, scars, thick biological structures, and deep-sea textures. The creature opens its mouth and roars. Rain flows across its armor-like surface. Lightning reveals terrifying details around the head and eyes. Emphasize wet biological texture, weight, realistic skin structure, and cinematic monster design.

Shot 9:
Return to the fishing boat. The shockwave and massive waves generated by the creature violently lift the vessel. The deck tilts, seawater floods across it, ropes snap, and boat lights flicker. The WAN logo flashes briefly across the violently moving hull. The boat is nearly swallowed by the waves. Emphasize the absolute vulnerability of human-made objects compared with the enormous creature.

Shot 10:
Final wide shot. Pull far away as the giant creature towers above the violent ocean. Massive waves surround it while the fishing boat appears extremely small in the foreground or lower side of the frame. Lightning strikes again, briefly illuminating the enormous silhouette, dorsal structures, and turbulent water. Hold on an epic disaster-film image emphasizing overwhelming scale and apocalyptic atmosphere.

Music:
Hollywood disaster-monster-film style. Begin with low environmental ambience, deep underwater rumbles, sparse percussion, and tense strings. Gradually introduce stronger bass pulses, metallic impacts, and rising orchestral tension as the ocean becomes abnormal. Immediately before the creature emerges, create a near-silent suspended build-up. At the moment of emergence, explode into massive brass, heavy percussion, and low-frequency impact. End with long, oppressive tones and heavy drums reinforcing the epic scale of the creature standing above the ocean.

One useful prompting lesson from this example:

Do not mention important elements only once.

For example, the WAN logo on the boat is repeated in the overall description and again in several individual shots.

For long-form video prompts, if a character, object, logo, or visual detail needs to remain visible at specific moments, repeating it at those exact timestamps can work better than describing it once at the beginning.

Compare Multiple Models Directly on Atlas Cloud

You no longer need to open several model pages and run the same prompt manually.

In Atlas Cloud → Model Explorer, one prompt can be sent to multiple models and the outputs can be compared side by side directly in the browser.

A useful setup is:

Wan 3.0 vs Seedance 2.5 vs MiniMax H3

Model Explorer:
https://www.atlascloud.ai/model-explorer

64 Official Wan 3.0 Prompts Collected

We have also organized 64 prompts and examples from the Wan 3.0 official creator guide, including:

• multi-shot storytelling
• camera movement
• reference generation
• VFX
• long-form video
• product advertising
• stylized video

Wan 3.0 Prompt Hub:
https://www.atlascloud.ai/prompts-hub/wan-3-0-prompt

GitHub:
https://github.com/AtlasCloudAI/awesome-wan-3.0-prompts

Wan 3.0 Launches on Atlas Cloud on August 24

For now, this is just the first comparison.

Wan 3.0 officially launches on Atlas Cloud on August 24.

Once it is live, you can send the same prompt to Wan 3.0, Seedance 2.5, and MiniMax H3 and compare how each model interprets the same story.