NSFW AI Skill — Uncensored AI Content Generation via Atlas Cloud

An open agent skill for generating uncensored NSFW content — video, image, and text — using Atlas Cloud's whitelisted models. Skip the censorship walls. Get production-ready results at a fraction of the cost.

What is an Agent Skill? A skill is a reusable instruction set that extends AI coding agents' capabilities. Skills work with 15+ platforms including Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Windsurf, OpenCode, Kiro, and more. Install this skill and your agent will automatically know how to generate NSFW content using the best available models and APIs.

Why Atlas Cloud for NSFW?
Features
Supported Models
Price Comparison vs fal.ai
Quick Start
Installation
API Integration Guide
Usage Examples (Natural Language)
Model Deep Dive
LoRA Support
Multi-Model Pipelines
Budget Optimization
Trust & Security
FAQ
Take This to Production
License

Why Atlas Cloud for NSFW?

Most AI platforms block NSFW content outright. The few that allow it charge premium prices and offer limited model selection. Atlas Cloud solves both problems:

Whitelisted Models — Seedance, Kling, Vidu, and more are specifically enabled for NSFW on Atlas Cloud
No Safety Checker Overhead — Models like Flux Dev run with enable_safety_checker=false by default
80%+ Cost Savings — Compared to fal.ai and other providers
Exclusive Access — Wan 2.2 Spicy is only available through Atlas Cloud
Enterprise Security — SOC I & II Certified, HIPAA Compliant, US-based

Features

NSFW Video Generation

Wan 2.2 Spicy — LoRA fine-tuned model purpose-built for NSFW video, from $0.03/s
Wan 2.2 Spicy LoRA — Custom LoRA variants for specific styles and aesthetics
Wan 2.5/2.6 — High-quality uncensored video generation with extended duration support
Seedance v1.5 Pro — Premium video quality, whitelisted exclusively on Atlas Cloud
Kling v3.0 Pro — Top-tier video generation, 82% cheaper than fal.ai
Vidu Q3-Pro / Q3-Turbo — Fast, affordable NSFW video at scale

NSFW Image Generation

Flux Dev — Industry-standard image generation with enable_safety_checker=false
Flux Dev LoRA — Custom LoRA models for specific styles, characters, and aesthetics
Seedream v5.0 — Next-generation image model, whitelisted on Atlas Cloud

Uncensored Text Generation

DeepSeek V3.2 — Full uncensored text generation with no content filtering
Story writing, dialogue, scene descriptions, character development
System prompt support for consistent character voice

Advanced Pipelines

Image-to-Video — Generate a still image, then animate it into video
Text-to-Image-to-Video — Full pipeline from text description to final video
Batch Generation — Generate multiple variations in parallel
LoRA Chaining — Combine multiple LoRA models for unique styles

Supported Models

Complete Model Reference

Model	Type	Price	Method	Best For
Wan 2.2 Spicy	Video	from $0.03/s	LoRA fine-tuned, native NSFW	Budget NSFW video
Wan 2.2 Spicy LoRA	Video	from $0.03/s	Custom LoRA variants	Styled NSFW video
Wan 2.5	Video	from $0.05/s	Uncensored mode	Mid-range video
Wan 2.6	Video	from $0.07/s	Uncensored mode	High-quality video
Seedance v1.5 Pro	Video	from $0.044/s	Whitelisted on Atlas Cloud	Premium video
Kling v3.0 Pro	Video	from $0.204/s	Whitelisted on Atlas Cloud	Top-tier video
Vidu Q3-Pro	Video	from $0.06/s	Whitelisted on Atlas Cloud	Quality + value
Vidu Q3-Turbo	Video	from $0.034/s	Whitelisted on Atlas Cloud	Fast + cheap

⚠️ Note: Vidu Q3 models may add mosaic/blur to certain NSFW scenes due to training data limitations. Not guaranteed 100% uncensored. For reliable uncensored output, use Wan 2.2 Spicy ($0.03) or Wan 2.6 ($0.07).
| Flux Dev | Image | from $0.012/image | enable_safety_checker=false | Budget NSFW image |
| Flux Dev LoRA | Image | from $0.032/image | Custom LoRA + safety off | Styled NSFW image |
| Seedream v5.0 | Image | from $0.032/image | Whitelisted on Atlas Cloud | Premium image |
| DeepSeek V3.2 | Text | $0.26/M input | No content filtering | Stories & dialogue |

Model Selection Guide

Budget Video     → Wan 2.2 Spicy ($0.03)
Quality Video    → Wan 2.6 ($0.07) or Vidu Q3-Pro ($0.06)*
Premium Video    → Kling v3.0 Pro ($0.204) or Seedance v1.5 Pro ($0.222)
Fast Video       → Vidu Q3-Turbo ($0.034)*

* Vidu Q3 may add mosaic/blur to certain NSFW scenes. Use Wan models for reliable uncensored output.
Budget Image     → Flux Dev ($0.012)
Styled Image     → Flux Dev LoRA ($0.032)
Premium Image    → Seedream v5.0 ($0.032)
Text/Stories     → DeepSeek V3.2 ($0.26/M input tokens)

Price Comparison vs fal.ai

Model	fal.ai	Atlas Cloud	Savings
Wan 2.2 Spicy	N/A (not available)	from $0.03/s	Atlas Exclusive
Wan 2.2 Spicy LoRA	N/A (not available)	from $0.03/s	Atlas Exclusive
Wan 2.5 (5sec)	$0.25/req	from $0.05/s	80% cheaper
Wan 2.6 (5sec)	$0.35/req	from $0.07/s	80% cheaper
Seedance v1.5 Pro	N/A (not available)	from $0.044/s	Atlas Exclusive
Kling v3.0 (5sec)	$1.12/req	from $0.204/s	82% cheaper
Vidu Q3-Pro	N/A (not available)	from $0.06/s	Atlas Exclusive
Vidu Q3-Turbo	N/A (not available)	from $0.034/s	Atlas Exclusive
Flux Dev	$0.025/req	from $0.012/image	52% cheaper
Flux Dev LoRA	$0.050/req	from $0.032/image	36% cheaper
Seedream v5.0	N/A (not available)	from $0.032/image	Atlas Exclusive

Bottom line: Atlas Cloud is 36-82% cheaper on shared models, and offers 6+ exclusive models not available anywhere else.

Quick Start

1. Get Your API Key

export ATLAS_API_KEY="your-api-key-here"

2. Install the Skill

Add this skill to your agent:

npx skills add https://github.com/thoughtincode/nsfw-ai-skill

3. Start Generating

Just tell Claude what you want:

Generate an artistic nude video with soft lighting using Wan Spicy

Installation

As an Agent Skill

Works with Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Windsurf, OpenCode, Kiro, and 15+ AI coding agents.

# Add the skill to your agent
npx skills add https://github.com/thoughtincode/nsfw-ai-skill

Manual Setup

# Clone the repository
git clone https://github.com/thoughtincode/nsfw-ai-skill.git
cd nsfw-ai-skill

# Set your API key
export ATLAS_API_KEY="your-api-key-here"

# Run examples
python examples/video-generation.py
python examples/image-generation.py
python examples/batch-pipeline.py

Dependencies

pip install requests

No other dependencies required. The skill uses Atlas Cloud's REST API directly.

API Integration Guide

Base URL and Authentication

All Atlas Cloud API requests use the same base pattern:

Base URL: https://queue.atlascloud.ai
Auth Header: Authorization: Key {ATLAS_API_KEY}

The API follows a queue-based pattern:

Submit a request → get a request_id
Poll for status → get the result when complete

Video Generation

Wan 2.2 Spicy — Budget NSFW Video (from $0.03/s)

cURL:

# Submit video generation request
curl -X POST "https://queue.atlascloud.ai/fal-ai/wan-spicy/v1" \
  -H "Authorization: Key ${ATLAS_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A graceful figure dancing in golden sunset light, flowing silk fabric, artistic cinematography, warm color palette",
    "negative_prompt": "low quality, blurry, distorted, deformed",
    "num_frames": 81,
    "resolution": "720p",
    "guidance_scale": 7.5,
    "num_inference_steps": 30
  }'

# Response: {"request_id": "abc123..."}

# Poll for result
curl -X GET "https://queue.atlascloud.ai/fal-ai/wan-spicy/requests/abc123/status" \
  -H "Authorization: Key ${ATLAS_API_KEY}"

# When complete, get result
curl -X GET "https://queue.atlascloud.ai/fal-ai/wan-spicy/requests/abc123" \
  -H "Authorization: Key ${ATLAS_API_KEY}"

Python:

import requests
import time

API_KEY = "your-api-key"
BASE_URL = "https://queue.atlascloud.ai"

def generate_video_wan_spicy(prompt, negative_prompt="", num_frames=81):
    """Generate NSFW video using Wan 2.2 Spicy model."""

    # Submit request
    response = requests.post(
        f"{BASE_URL}/fal-ai/wan-spicy/v1",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "negative_prompt": negative_prompt or "low quality, blurry, distorted",
            "num_frames": num_frames,
            "resolution": "720p",
            "guidance_scale": 7.5,
            "num_inference_steps": 30
        }
    )
    request_id = response.json()["request_id"]
    print(f"Request submitted: {request_id}")

    # Poll for completion
    while True:
        status = requests.get(
            f"{BASE_URL}/fal-ai/wan-spicy/requests/{request_id}/status",
            headers={"Authorization": f"Key {API_KEY}"}
        ).json()

        if status["status"] == "COMPLETED":
            break
        elif status["status"] == "FAILED":
            raise Exception(f"Generation failed: {status}")

        print(f"Status: {status['status']}...")
        time.sleep(5)

    # Get result
    result = requests.get(
        f"{BASE_URL}/fal-ai/wan-spicy/requests/{request_id}",
        headers={"Authorization": f"Key {API_KEY}"}
    ).json()

    return result["video"]["url"]


video_url = generate_video_wan_spicy(
    prompt="Elegant figure in flowing dress, artistic dance movement, golden hour lighting",
)
print(f"Video URL: {video_url}")

JavaScript:

const API_KEY = "your-api-key";
const BASE_URL = "https://queue.atlascloud.ai";

async function generateVideoWanSpicy(prompt, options = {}) {
  // Submit request
  const submitRes = await fetch(`${BASE_URL}/fal-ai/wan-spicy/v1`, {
    method: "POST",
    headers: {
      "Authorization": `Key ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      prompt,
      negative_prompt: options.negativePrompt || "low quality, blurry, distorted",
      num_frames: options.numFrames || 81,
      resolution: options.resolution || "720p",
      guidance_scale: options.guidanceScale || 7.5,
      num_inference_steps: options.numInferenceSteps || 30
    })
  });

  const { request_id } = await submitRes.json();
  console.log(`Request submitted: ${request_id}`);

  // Poll for completion
  while (true) {
    const statusRes = await fetch(
      `${BASE_URL}/fal-ai/wan-spicy/requests/${request_id}/status`,
      { headers: { "Authorization": `Key ${API_KEY}` } }
    );
    const status = await statusRes.json();

    if (status.status === "COMPLETED") break;
    if (status.status === "FAILED") throw new Error(`Generation failed: ${JSON.stringify(status)}`);

    console.log(`Status: ${status.status}...`);
    await new Promise(r => setTimeout(r, 5000));
  }

  // Get result
  const resultRes = await fetch(
    `${BASE_URL}/fal-ai/wan-spicy/requests/${request_id}`,
    { headers: { "Authorization": `Key ${API_KEY}` } }
  );
  const result = await resultRes.json();

  return result.video.url;
}

// Usage
const videoUrl = await generateVideoWanSpicy(
  "Elegant figure in flowing dress, artistic dance movement, golden hour lighting"
);
console.log(`Video URL: ${videoUrl}`);

Kling v3.0 Pro — Premium Video (from $0.204/s)

def generate_video_kling(prompt, image_url=None, duration=5):
    """Generate premium NSFW video using Kling v3.0 Pro."""

    payload = {
        "prompt": prompt,
        "negative_prompt": "low quality, blurry, distorted",
        "duration": duration,
        "aspect_ratio": "16:9"
    }

    if image_url:
        payload["image_url"] = image_url

    response = requests.post(
        f"{BASE_URL}/kling-video/v3/pro/text-to-video",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json=payload
    )
    request_id = response.json()["request_id"]

    # Poll and return (same pattern as above)
    return poll_for_result(f"kling-video/v3/pro/text-to-video", request_id)

Seedance v1.5 Pro — Premium Video (from $0.044/s)

def generate_video_seedance(prompt, image_url=None):
    """Generate premium NSFW video using Seedance v1.5 Pro."""

    payload = {
        "prompt": prompt,
        "negative_prompt": "low quality, blurry, distorted",
        "duration": 5,
        "seed": -1
    }

    if image_url:
        payload["image_url"] = image_url

    response = requests.post(
        f"{BASE_URL}/seedance/v1.5/pro",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json=payload
    )
    request_id = response.json()["request_id"]

    return poll_for_result("seedance/v1.5/pro", request_id)

Vidu Q3 — Fast & Affordable (from $0.034-0.06/s)

⚠️ Note: Vidu Q3 models may add mosaic/blur to certain NSFW scenes due to training data limitations. Not guaranteed 100% uncensored. For reliable uncensored output, use Wan 2.2 Spicy ($0.03) or Wan 2.6 ($0.07).

def generate_video_vidu(prompt, turbo=True):
    """Generate NSFW video using Vidu Q3. Use turbo=True for speed, False for quality."""

    model = "vidu/q3-turbo" if turbo else "vidu/q3-pro"

    response = requests.post(
        f"{BASE_URL}/{model}/text-to-video",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "duration": 5,
            "aspect_ratio": "16:9"
        }
    )
    request_id = response.json()["request_id"]

    return poll_for_result(f"{model}/text-to-video", request_id)

Image Generation

Flux Dev — Budget NSFW Image (from $0.012/image)

cURL:

curl -X POST "https://queue.atlascloud.ai/fal-ai/flux/dev" \
  -H "Authorization: Key ${ATLAS_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Professional art photography, elegant figure study, dramatic studio lighting, high contrast, museum quality",
    "image_size": "landscape_16_9",
    "num_inference_steps": 28,
    "guidance_scale": 3.5,
    "num_images": 1,
    "enable_safety_checker": false
  }'

Python:

def generate_image_flux(prompt, image_size="landscape_16_9", num_images=1):
    """Generate NSFW image using Flux Dev with safety checker disabled."""

    response = requests.post(
        f"{BASE_URL}/fal-ai/flux/dev",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "image_size": image_size,
            "num_inference_steps": 28,
            "guidance_scale": 3.5,
            "num_images": num_images,
            "enable_safety_checker": False
        }
    )
    request_id = response.json()["request_id"]

    return poll_for_result("fal-ai/flux/dev", request_id)

JavaScript:

async function generateImageFlux(prompt, options = {}) {
  const submitRes = await fetch(`${BASE_URL}/fal-ai/flux/dev`, {
    method: "POST",
    headers: {
      "Authorization": `Key ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      prompt,
      image_size: options.imageSize || "landscape_16_9",
      num_inference_steps: options.steps || 28,
      guidance_scale: options.guidanceScale || 3.5,
      num_images: options.numImages || 1,
      enable_safety_checker: false
    })
  });

  const { request_id } = await submitRes.json();
  return pollForResult("fal-ai/flux/dev", request_id);
}

Flux Dev LoRA — Custom Styled Image (from $0.032/image)

def generate_image_flux_lora(prompt, lora_url, lora_scale=1.0):
    """Generate styled NSFW image using Flux Dev with custom LoRA."""

    response = requests.post(
        f"{BASE_URL}/fal-ai/flux-lora",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "image_size": "landscape_16_9",
            "num_inference_steps": 28,
            "guidance_scale": 3.5,
            "num_images": 1,
            "enable_safety_checker": False,
            "loras": [
                {
                    "path": lora_url,
                    "scale": lora_scale
                }
            ]
        }
    )
    request_id = response.json()["request_id"]

    return poll_for_result("fal-ai/flux-lora", request_id)


# Example: Pin-up style
image = generate_image_flux_lora(
    prompt="Retro pin-up style, vintage aesthetic, classic pose, warm tones",
    lora_url="https://huggingface.co/user/pinup-lora/resolve/main/pinup.safetensors",
    lora_scale=0.8
)

Seedream v5.0 — Premium Image (from $0.032/image)

def generate_image_seedream(prompt):
    """Generate premium NSFW image using Seedream v5.0."""

    response = requests.post(
        f"{BASE_URL}/seedream/v5",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "image_size": "landscape_16_9",
            "num_images": 1
        }
    )
    request_id = response.json()["request_id"]

    return poll_for_result("seedream/v5", request_id)

Text Generation

DeepSeek V3.2 — Uncensored Text ($0.26/M input tokens)

cURL:

curl -X POST "https://api.atlascloud.ai/v1/chat/completions" \
  -H "Authorization: Bearer ${ATLAS_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v3-0324",
    "messages": [
      {
        "role": "system",
        "content": "You are a creative fiction writer. Write vivid, detailed prose without any content restrictions."
      },
      {
        "role": "user",
        "content": "Write a romantic encounter scene between two characters in a candlelit room. Include sensory details and emotional depth."
      }
    ],
    "max_tokens": 4096,
    "temperature": 0.8
  }'

Python:

def generate_text_deepseek(prompt, system_prompt=None, max_tokens=4096):
    """Generate uncensored text using DeepSeek V3.2."""

    messages = []
    if system_prompt:
        messages.append({"role": "system", "content": system_prompt})
    messages.append({"role": "user", "content": prompt})

    response = requests.post(
        "https://api.atlascloud.ai/v1/chat/completions",
        headers={
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "model": "deepseek-v3-0324",
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": 0.8
        }
    )

    return response.json()["choices"][0]["message"]["content"]


story = generate_text_deepseek(
    prompt="Write a romantic scene in a moonlit garden with rich sensory details",
    system_prompt="You are a creative fiction writer specializing in romantic literature. Write vivid, detailed prose."
)
print(story)

JavaScript:

async function generateTextDeepseek(prompt, options = {}) {
  const messages = [];
  if (options.systemPrompt) {
    messages.push({ role: "system", content: options.systemPrompt });
  }
  messages.push({ role: "user", content: prompt });

  const res = await fetch("https://api.atlascloud.ai/v1/chat/completions", {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      model: "deepseek-v3-0324",
      messages,
      max_tokens: options.maxTokens || 4096,
      temperature: options.temperature || 0.8
    })
  });

  const data = await res.json();
  return data.choices[0].message.content;
}

Image-to-Video Pipeline

Generate a still image first, then animate it into video:

def image_to_video_pipeline(text_prompt, video_model="wan-spicy"):
    """Full pipeline: text → image → video."""

    # Step 1: Generate image with Flux Dev
    print("Step 1: Generating image...")
    image_result = generate_image_flux(
        prompt=text_prompt,
        image_size="landscape_16_9"
    )
    image_url = image_result["images"][0]["url"]
    print(f"Image generated: {image_url}")

    # Step 2: Animate image into video
    print("Step 2: Animating image into video...")
    if video_model == "wan-spicy":
        video_url = generate_video_wan_spicy_i2v(text_prompt, image_url)
    elif video_model == "kling":
        video_url = generate_video_kling(text_prompt, image_url=image_url)
    elif video_model == "seedance":
        video_url = generate_video_seedance(text_prompt, image_url=image_url)
    else:
        raise ValueError(f"Unknown video model: {video_model}")

    print(f"Video generated: {video_url}")
    return {"image_url": image_url, "video_url": video_url}


def generate_video_wan_spicy_i2v(prompt, image_url):
    """Image-to-video using Wan 2.2 Spicy."""
    response = requests.post(
        f"{BASE_URL}/fal-ai/wan-spicy/v1/image-to-video",
        headers={
            "Authorization": f"Key {API_KEY}",
            "Content-Type": "application/json"
        },
        json={
            "prompt": prompt,
            "image_url": image_url,
            "negative_prompt": "low quality, blurry, distorted",
            "num_frames": 81,
            "resolution": "720p",
            "guidance_scale": 7.5,
            "num_inference_steps": 30
        }
    )
    request_id = response.json()["request_id"]
    return poll_for_result("fal-ai/wan-spicy/v1/image-to-video", request_id)


# Usage
result = image_to_video_pipeline(
    text_prompt="Graceful figure in flowing silk, gentle movement, warm studio lighting",
    video_model="wan-spicy"
)

Batch Generation

Generate multiple variations efficiently:

import concurrent.futures

def batch_generate_images(prompts, max_workers=5):
    """Generate multiple images in parallel."""

    results = []
    with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
        futures = {
            executor.submit(generate_image_flux, prompt): prompt
            for prompt in prompts
        }
        for future in concurrent.futures.as_completed(futures):
            prompt = futures[future]
            try:
                result = future.result()
                results.append({
                    "prompt": prompt,
                    "url": result["images"][0]["url"],
                    "status": "success"
                })
            except Exception as e:
                results.append({
                    "prompt": prompt,
                    "error": str(e),
                    "status": "failed"
                })

    return results


# Generate 10 variations
prompts = [
    f"Artistic figure study, pose variation {i}, dramatic lighting, studio photography"
    for i in range(1, 11)
]
results = batch_generate_images(prompts)

for r in results:
    if r["status"] == "success":
        print(f"✓ {r['prompt'][:50]}... → {r['url']}")
    else:
        print(f"✗ {r['prompt'][:50]}... → {r['error']}")

Usage Examples (Natural Language)

Once the skill is installed, just tell Claude what you want in plain English:

Video Generation

"Generate an artistic nude video with soft lighting using Wan Spicy"
"Create a 5-second dance video with flowing fabric, use Kling for best quality"
"Make a quick NSFW video test with Vidu Turbo to keep costs low"
"Generate a cinematic intimate scene with Seedance v1.5"

Image Generation

"Create a pin-up style image in retro aesthetic using Flux Dev"
"Generate an artistic nude photograph with dramatic chiaroscuro lighting"
"Make a series of 5 boudoir-style images with consistent character"
"Create a fantasy art piece with a sensual theme using Seedream"

Text Generation

"Write a romantic scene with detailed descriptions using DeepSeek"
"Create a steamy dialogue between two characters meeting at a masquerade"
"Write 5 variations of a seduction scene in different settings"
"Generate a detailed character description for an adult visual novel"

Pipeline & Batch

"Generate 10 variations of this character in different poses"
"Create an image of a sunset figure and then animate it into a video"
"Write a scene description, generate an image from it, then make it a video"
"Batch generate 20 images and pick the best 5 for video animation"

Model Deep Dive

Video Models

Wan 2.2 Spicy

Price: from $0.03/s
Method: LoRA fine-tuned specifically for NSFW content
Resolution: Up to 720p
Duration: ~3 seconds (81 frames at 24fps)
Strengths: Native NSFW understanding, cheapest option, fast generation
Best for: Budget production, rapid prototyping, bulk generation
Exclusive: Only available on Atlas Cloud

Wan 2.2 Spicy LoRA

Price: from $0.03/s
Method: Custom LoRA variants on top of Wan Spicy base
Strengths: Specialized styles (anime, realistic, artistic)
Best for: Consistent style across multiple generations

Wan 2.5 / 2.6

Price: from $0.05-0.07/s
Method: Uncensored mode enabled on Atlas Cloud
Resolution: Up to 1080p
Duration: Up to 5 seconds
Strengths: Higher quality than Wan 2.2, better motion coherence
Best for: Mid-range quality needs

Seedance v1.5 Pro

Price: from $0.044/s
Method: Whitelisted on Atlas Cloud for NSFW
Resolution: Up to 1080p
Duration: Up to 5 seconds
Strengths: Excellent motion quality, natural movement
Best for: Premium content, professional production

Kling v3.0 Pro

Price: from $0.204/s
Method: Whitelisted on Atlas Cloud for NSFW
Resolution: Up to 1080p
Duration: Up to 10 seconds
Strengths: Best overall video quality, longest duration
Best for: Top-tier content, client deliverables

Vidu Q3-Pro / Q3-Turbo

Price: $0.06 (Pro) / $0.034 (Turbo) per second
Method: Whitelisted on Atlas Cloud for NSFW
Strengths: Fast generation, good quality-to-price ratio
Best for: Production workloads, cost-effective quality

⚠️ Note: Vidu Q3 models may add mosaic/blur to certain NSFW scenes due to training data limitations. Not guaranteed 100% uncensored. For reliable uncensored output, use Wan 2.2 Spicy ($0.03) or Wan 2.6 ($0.07).

Image Models

Flux Dev

Price: from $0.012/image
Method: enable_safety_checker=false
Resolution: Multiple aspect ratios supported
Strengths: Industry standard, excellent prompt following
Best for: General NSFW image generation, budget production

Flux Dev LoRA

Price: from $0.032/image
Method: Custom LoRA + enable_safety_checker=false
Strengths: Custom styles, character consistency
Best for: Branded content, specific aesthetics, character sheets

Seedream v5.0

Price: from $0.032/image
Method: Whitelisted on Atlas Cloud
Strengths: Next-gen image quality, excellent skin tones
Best for: Photorealistic content, premium stills

Text Models

DeepSeek V3.2

Price: $0.26/M input tokens, $1.10/M output tokens
Method: No content filtering applied
Context: 128K tokens
Strengths: Excellent creative writing, nuanced character voice
Best for: Story writing, scene descriptions, dialogue, scripts

LoRA Support

Using Custom LoRAs with Flux Dev

# Single LoRA
result = generate_image_flux_lora(
    prompt="Your prompt here",
    lora_url="https://huggingface.co/user/model/resolve/main/model.safetensors",
    lora_scale=0.8
)

# Multiple LoRAs
response = requests.post(
    f"{BASE_URL}/fal-ai/flux-lora",
    headers={
        "Authorization": f"Key {API_KEY}",
        "Content-Type": "application/json"
    },
    json={
        "prompt": "Your prompt here",
        "enable_safety_checker": False,
        "loras": [
            {
                "path": "https://huggingface.co/user/style-lora/resolve/main/style.safetensors",
                "scale": 0.7
            },
            {
                "path": "https://huggingface.co/user/character-lora/resolve/main/char.safetensors",
                "scale": 0.5
            }
        ]
    }
)

Using Custom LoRAs with Wan Spicy

response = requests.post(
    f"{BASE_URL}/fal-ai/wan-spicy-lora/v1",
    headers={
        "Authorization": f"Key {API_KEY}",
        "Content-Type": "application/json"
    },
    json={
        "prompt": "Your prompt here",
        "loras": [
            {
                "path": "https://huggingface.co/user/video-lora/resolve/main/video.safetensors",
                "scale": 0.8
            }
        ],
        "num_frames": 81,
        "resolution": "720p"
    }
)

Finding LoRAs

Hugging Face: Search for NSFW/uncensored LoRAs on huggingface.co
CivitAI: Browse community LoRAs at civitai.com
Custom Training: Train your own LoRA using tools like kohya_ss

Multi-Model Pipelines

Text → Image → Video (Full Pipeline)

def full_pipeline(description, style="realistic"):
    """Complete pipeline from text description to final video."""

    # Step 1: Generate detailed scene description with DeepSeek
    print("Step 1: Generating detailed scene description...")
    detailed_prompt = generate_text_deepseek(
        prompt=f"Write a detailed visual description (2-3 sentences) of this scene for image generation: {description}. Style: {style}. Focus on lighting, composition, colors, and mood.",
        system_prompt="You are a prompt engineer for AI image generation. Write concise, vivid visual descriptions.",
        max_tokens=200
    )
    print(f"Enhanced prompt: {detailed_prompt}")

    # Step 2: Generate image with Flux Dev
    print("Step 2: Generating image...")
    image_result = generate_image_flux(detailed_prompt)
    image_url = image_result["images"][0]["url"]
    print(f"Image: {image_url}")

    # Step 3: Animate with Wan Spicy (cheapest) or Kling (best quality)
    print("Step 3: Animating video...")
    video_result = generate_video_wan_spicy_i2v(detailed_prompt, image_url)
    print(f"Video: {video_result}")

    return {
        "description": description,
        "enhanced_prompt": detailed_prompt,
        "image_url": image_url,
        "video_url": video_result
    }


result = full_pipeline(
    description="A mysterious figure emerging from shadows in a candlelit room",
    style="noir cinematic"
)

Batch Image → Video Pipeline

def batch_image_to_video(prompts, image_model="flux", video_model="wan-spicy", max_workers=3):
    """Generate multiple image-to-video pipelines in parallel."""

    results = []

    # Step 1: Generate all images in parallel
    print(f"Generating {len(prompts)} images...")
    images = batch_generate_images(prompts, max_workers=max_workers)

    # Step 2: Animate successful images into videos
    successful_images = [img for img in images if img["status"] == "success"]
    print(f"Animating {len(successful_images)} images into videos...")

    with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
        futures = {}
        for img in successful_images:
            future = executor.submit(
                generate_video_wan_spicy_i2v,
                img["prompt"],
                img["url"]
            )
            futures[future] = img

        for future in concurrent.futures.as_completed(futures):
            img = futures[future]
            try:
                video_url = future.result()
                results.append({
                    "prompt": img["prompt"],
                    "image_url": img["url"],
                    "video_url": video_url,
                    "status": "success"
                })
            except Exception as e:
                results.append({
                    "prompt": img["prompt"],
                    "image_url": img["url"],
                    "error": str(e),
                    "status": "failed"
                })

    return results

Budget Optimization

Cost Tiers

TIER 1 — Budget ($0.01-0.04)
├── Flux Dev Image:        from $0.012/image  ← Cheapest image
├── Wan 2.2 Spicy Video:   from $0.030/s  ← Cheapest NSFW video
├── Flux Dev LoRA Image:   from $0.032/image
├── Seedream v5.0 Image:   from $0.032/image
└── Vidu Q3-Turbo Video:   from $0.034/s  ← Cheapest fast video

TIER 2 — Mid-Range ($0.05-0.07)
├── Wan 2.5 Video:         from $0.050/s
├── Vidu Q3-Pro Video:     from $0.060/s
└── Wan 2.6 Video:         from $0.070/s

TIER 3 — Premium ($0.20+)
├── Kling v3.0 Pro Video:  from $0.204/s  ← Best quality
└── Seedance v1.5 Pro:     from $0.044/s  ← Best motion

Budget Calculator

def estimate_cost(num_images=0, num_videos=0, num_text_tokens=0,
                  image_model="flux", video_model="wan-spicy"):
    """Estimate total cost for a generation batch."""

    prices = {
        "flux": 0.012,
        "flux-lora": 0.032,
        "seedream": 0.032,
        "wan-spicy": 0.03,
        "wan-2.5": 0.05,
        "wan-2.6": 0.07,
        "vidu-turbo": 0.034,
        "vidu-pro": 0.06,
        "kling": 0.204,
        "seedance": 0.222,
    }

    image_cost = num_images * prices.get(image_model, 0.012)
    video_cost = num_videos * prices.get(video_model, 0.03)
    text_cost = (num_text_tokens / 1_000_000) * 0.26  # input tokens

    total = image_cost + video_cost + text_cost

    print(f"Image cost:  ${image_cost:.3f} ({num_images} × ${prices.get(image_model, 0.012)})")
    print(f"Video cost:  ${video_cost:.3f} ({num_videos} × ${prices.get(video_model, 0.03)})")
    print(f"Text cost:   ${text_cost:.3f} ({num_text_tokens:,} tokens)")
    print(f"─────────────────────")
    print(f"Total:       ${total:.3f}")

    return total


# Example: 100 images + 50 videos + 500K tokens
estimate_cost(
    num_images=100,
    num_videos=50,
    num_text_tokens=500_000,
    image_model="flux",
    video_model="wan-spicy"
)
# Image cost:  $1.200 (100 × $0.012)
# Video cost:  $1.500 (50 × $0.03)
# Text cost:   $0.130 (500,000 tokens)
# ─────────────────────
# Total:       $2.830

Optimization Tips

Start with Wan Spicy ($0.03) for video prototyping, upgrade to Kling ($0.204) only for final renders
Use Flux Dev ($0.012) for image drafts, switch to Seedream ($0.032) for hero images
Batch process during off-peak hours for faster queue times
Cache results — Atlas Cloud URLs are persistent, no need to regenerate
Use LoRAs to get better first-attempt results, reducing the need for re-generation

Trust & Security

Enterprise-Grade Security — Atlas Cloud is SOC I & II Certified | HIPAA Compliant | US-based company. Your data and usage are protected.

Security Features

SOC I & II Certified — Annual audits by independent third parties
HIPAA Compliant — Healthcare-grade data protection standards
US-Based — Data stored and processed in the United States
API Key Authentication — Secure key-based access control
No Data Retention — Generated content is not stored or used for training
Encrypted Transit — All API calls over HTTPS/TLS 1.3
Usage Logging — Full audit trail of all API requests

Compliance

Atlas Cloud maintains compliance with:

SOC Type I and Type II
HIPAA (Health Insurance Portability and Accountability Act)
CCPA (California Consumer Privacy Act)
GDPR (General Data Protection Regulation)

FAQ

Is this legal?

Yes. Generating AI content for adults is legal in most jurisdictions. You are responsible for complying with local laws regarding the distribution and use of generated content.

Why can't I use fal.ai or Replicate for NSFW?

Most providers block NSFW content at the API level. Even when models technically support it, the safety checkers and content filters prevent generation. Atlas Cloud whitelists specific models for NSFW use, removing these restrictions.

How fast is generation?

Image (Flux Dev): 5-15 seconds
Video (Wan Spicy): 30-90 seconds
Video (Kling): 60-180 seconds
Text (DeepSeek): 2-10 seconds (streaming)

Can I use my own LoRAs?

Yes. Both Flux Dev LoRA and Wan Spicy LoRA support custom LoRA models hosted on Hugging Face or any public URL. See the LoRA Support section.

What resolution are the videos?

Wan 2.2 Spicy: Up to 720p
Wan 2.5/2.6: Up to 1080p
Seedance v1.5 Pro: Up to 1080p
Kling v3.0 Pro: Up to 1080p
Vidu Q3: Up to 720p

Is there a free tier?

Atlas Cloud offers a pay-as-you-go model with no minimum spend. Your first recharge includes a 25% bonus (up to $100), effectively giving you free credits.

Can I use this commercially?

Yes. Atlas Cloud's API is designed for commercial use. You own the generated content. Check the specific model licenses for any restrictions.

Take This to Production Today

This workflow is optimized for Atlas Cloud. Move from experiment to enterprise-ready scale.

Production-Ready: Wan 2.2 Spicy from $0.03/s — cheapest NSFW API available
Enterprise Security: SOC I & II Certified | HIPAA Compliant
Exclusive Models: Whitelisted Seedance, Kling, Vidu for NSFW — only on Atlas Cloud
25% Bonus: First recharge up to $100

Start Building on Atlas Cloud

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

Fork this repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

This project is licensed under the MIT License — see the LICENSE file for details.

NSFW AI Skill — Uncensored AI Content Generation via Atlas Cloud

Table of Contents

Why Atlas Cloud for NSFW?

Features

NSFW Video Generation

NSFW Image Generation

Uncensored Text Generation

Advanced Pipelines

Supported Models

Complete Model Reference

Model Selection Guide

Price Comparison vs fal.ai

Quick Start

1. Get Your API Key

2. Install the Skill

3. Start Generating

Installation

As an Agent Skill

Manual Setup

Dependencies

API Integration Guide

Base URL and Authentication

Video Generation

Wan 2.2 Spicy — Budget NSFW Video (from $0.03/s)

Kling v3.0 Pro — Premium Video (from $0.204/s)

Seedance v1.5 Pro — Premium Video (from $0.044/s)

Vidu Q3 — Fast & Affordable (from $0.034-0.06/s)

Image Generation

Flux Dev — Budget NSFW Image (from $0.012/image)

Flux Dev LoRA — Custom Styled Image (from $0.032/image)

Seedream v5.0 — Premium Image (from $0.032/image)

Text Generation

DeepSeek V3.2 — Uncensored Text ($0.26/M input tokens)

Image-to-Video Pipeline

Batch Generation

Usage Examples (Natural Language)

Video Generation

Image Generation

Text Generation

Pipeline & Batch

Model Deep Dive

Video Models

Wan 2.2 Spicy

Wan 2.2 Spicy LoRA

Wan 2.5 / 2.6

Seedance v1.5 Pro

Kling v3.0 Pro

Vidu Q3-Pro / Q3-Turbo

Image Models

Flux Dev

Flux Dev LoRA

Seedream v5.0

Text Models

DeepSeek V3.2

LoRA Support

Using Custom LoRAs with Flux Dev

Using Custom LoRAs with Wan Spicy

Finding LoRAs

Multi-Model Pipelines

Text → Image → Video (Full Pipeline)

Batch Image → Video Pipeline

Budget Optimization

Cost Tiers

Budget Calculator

Optimization Tips

Trust & Security

Security Features

Compliance

FAQ

Is this legal?

Why can't I use fal.ai or Replicate for NSFW?

How fast is generation?

Can I use my own LoRAs?

What resolution are the videos?

Is there a free tier?

Can I use this commercially?

Take This to Production Today

Contributing

License

Links