Recraft V3

Overview

Recraft V3 is the revolutionary AI image generation model released on October 30, 2025, that immediately claimed the #1 position on Hugging Face's Text-to-Image Benchmark by Artificial Analysis with an impressive ELO rating of 1172. What sets Recraft V3 apart is its unique focus on design-centric image generation, making it the only model in the world capable of generating images with long, complex text - not just one or two words, but full sentences and paragraphs with precise positioning.

Unlike competitors such as Midjourney and DALL-E 3, Recraft V3 offers comprehensive vector art support alongside traditional raster generation, making it invaluable for designers who need scalable graphics for logos, icons, illustrations, and branding materials. The model provides unprecedented control over text size, positioning, and styling within generated images, along with advanced features including precise style control, improved inpainting for editing specific regions, and new outpainting capabilities for extending images.

Available across desktop (Canvas), mobile (iOS and Android), and via API, Recraft V3 serves both free and professional users with transparent, affordable pricing: $0.04 per raster image and $0.08 per vector image.

Key Features

• #1 on Hugging Face Text-to-Image Benchmark (ELO 1172)
• Only model supporting long, complex text generation in images
• Vector and raster image generation support
• Precise text size and position control within images
• Advanced style control for consistent brand aesthetics
• Improved inpainting for selective image editing
• New outpainting capabilities for image extension
• Design-centric optimization for professional graphics
• Cross-platform: desktop app, mobile (iOS/Android), API
• Transparent pricing: $0.04/raster, $0.08/vector
• Free tier available for all users

Use Cases

• Logo and brand identity design
• Icon and UI element creation
• Marketing materials with text overlays
• Social media graphics with captions
• Poster and flyer design
• Infographic generation
• Vector illustrations for scalable graphics
• Product mockups and presentations
• Editorial and magazine layout elements
• Advertising creative with precise text placement
• Brand asset generation with consistent styling

Technical Specifications

Recraft V3 uses a proprietary diffusion model optimized for design. It outputs both raster (PNG, JPG) and vector (SVG) formats. The model features advanced text capabilities including long text support (full sentences/paragraphs), precise text placement control, adjustable text size, and font and style control. It achieved the #1 rank on Hugging Face's Text-to-Image Benchmark with an ELO rating of 1172 evaluated by Artificial Analysis. Available on desktop (Canvas web app), mobile (iOS and Android apps), and via RESTful API.

Pricing and Availability

Recraft V3 operates on a freemium model with transparent per-image pricing. A free tier is available with limited generations. Raster images cost $0.04 per image and vector images cost $0.08 per image. Pro plans are available for high-volume users, and API pricing is also available. This makes it one of the most affordable professional AI image generators.

Code Example: Cloud API Inference with Replicate

Recraft V3 is available exclusively through cloud APIs, optimized for design-focused applications. This example demonstrates integration with Replicate for generating images with precise text placement and vector graphics support.

import requests
import os
import time
import replicate
from pathlib import Path
import json

# Replicate API Configuration
os.environ["REPLICATE_API_TOKEN"] = "r8_your_api_token_here"

def generate_image_recraft(prompt, style="realistic_image", size="1024x1024", 
                          output_format="png", text_elements=None):
    """
    Generate design-focused images with Recraft V3
    
    Args:
        prompt: Text description of the image
        style: Visual style (realistic_image, digital_illustration, vector_illustration, etc.)
        size: Image dimensions (1024x1024, 1365x1024, 1024x1365, 1536x1024, etc.)
        output_format: Output format (png, jpg, webp, svg for vector styles)
        text_elements: Optional dict with text to place in image
    
    Returns:
        Path to downloaded image file
    """
    try:
        print(f"Generating with Recraft V3 ({style})...")
        print(f"Prompt: {prompt}")
        
        # Build input parameters
        input_params = {
            "prompt": prompt,
            "style": style,
            "size": size,
            "output_format": output_format
        }
        
        # Add text placement if specified
        if text_elements:
            input_params["text_content"] = text_elements["content"]
            input_params["text_position"] = text_elements.get("position", "center")
            input_params["text_size"] = text_elements.get("size", "large")
        
        start_time = time.time()
        
        # Run generation
        output = replicate.run(
            "recraft-ai/recraft-v3",
            input=input_params
        )
        
        generation_time = time.time() - start_time
        print(f"Generation time: {generation_time:.2f}s")
        
        # Download image from URL
        image_url = output[0] if isinstance(output, list) else output
        img_response = requests.get(image_url)
        img_response.raise_for_status()
        
        extension = output_format if output_format != "jpg" else "jpeg"
        output_path = Path(f"recraft_v3_{int(time.time())}.{extension}")
        
        with open(output_path, "wb") as f:
            f.write(img_response.content)
        
        print(f"Image downloaded to: {output_path}")
        return output_path
        
    except replicate.exceptions.ReplicateError as e:
        print(f"Replicate API error: {e}")
        raise
    except Exception as e:
        print(f"Unexpected error: {e}")
        raise

# Recraft Official API (direct REST integration)
RECRAFT_API_KEY = os.environ.get("RECRAFT_API_KEY", "your_api_key_here")
RECRAFT_API_URL = "https://external.api.recraft.ai/v1/images/generations"

def generate_image_recraft_api(prompt, style="realistic_image", size=1024, 
                               n_images=1, text_config=None):
    """
    Generate images using Recraft's official REST API
    
    Args:
        prompt: Text description
        style: Visual style preset
        size: Image size (512, 1024, 1536, 2048)
        n_images: Number of images to generate (1-4)
        text_config: Dict with text placement configuration
    
    Returns:
        List of image URLs
    """
    try:
        headers = {
            "Authorization": f"Bearer {RECRAFT_API_KEY}",
            "Content-Type": "application/json"
        }
        
        payload = {
            "prompt": prompt,
            "style": style,
            "size": size,
            "n": n_images,
            "response_format": "url"
        }
        
        # Add text configuration if provided
        if text_config:
            payload["text"] = text_config
        
        print(f"Submitting generation request to Recraft API...")
        print(f"Prompt: {prompt}")
        print(f"Style: {style}, Size: {size}x{size}")
        
        response = requests.post(RECRAFT_API_URL, headers=headers, json=payload)
        response.raise_for_status()
        
        result = response.json()
        
        image_urls = [img["url"] for img in result["data"]]
        print(f"Generated {len(image_urls)} images")
        
        # Download all images
        downloaded_paths = []
        for idx, url in enumerate(image_urls):
            img_response = requests.get(url)
            img_response.raise_for_status()
            
            output_path = Path(f"recraft_api_{int(time.time())}_{idx}.png")
            with open(output_path, "wb") as f:
                f.write(img_response.content)
            
            downloaded_paths.append(output_path)
            print(f"Image {idx+1} saved to: {output_path}")
        
        return downloaded_paths
        
    except requests.exceptions.RequestException as e:
        print(f"API error: {e}")
        if hasattr(e.response, 'text'):
            print(f"Response: {e.response.text}")
        raise
    except Exception as e:
        print(f"Unexpected error: {e}")
        raise

# Business use cases
if __name__ == "__main__":
    # Example 1: Logo design with vector output
    print("\nExample 1: Logo Design")
    logo_prompt = "Modern tech startup logo with abstract geometric shapes, minimalist design, blue and purple gradient"
    logo_image = generate_image_recraft(
        prompt=logo_prompt,
        style="vector_illustration",
        size="1024x1024",
        output_format="svg"  # Vector format for scalability
    )
    
    # Example 2: Marketing poster with text overlay
    print("\nExample 2: Marketing Poster with Text")
    poster_prompt = "Summer sale background with tropical leaves and vibrant colors, modern design aesthetic"
    poster_image = generate_image_recraft(
        prompt=poster_prompt,
        style="digital_illustration",
        size="1024x1365",  # Portrait orientation
        text_elements={
            "content": "SUMMER SALE\n50% OFF",
            "position": "top_center",
            "size": "xlarge"
        }
    )
    
    # Example 3: Social media graphics batch
    print("\nExample 3: Social Media Graphics Batch")
    social_prompts = [
        "Instagram story background with pastel gradient and floral elements",
        "LinkedIn post graphic with professional corporate aesthetic",
        "Facebook cover image with team collaboration theme, modern office"
    ]
    
    for idx, social_prompt in enumerate(social_prompts, 1):
        print(f"\nGenerating social graphic {idx}/{len(social_prompts)}...")
        image = generate_image_recraft(
            prompt=social_prompt,
            style="realistic_image",
            size="1024x1024"
        )
    
    # Example 4: Product mockup with text (Official API)
    print("\nExample 4: Product Mockup with Text")
    product_images = generate_image_recraft_api(
        prompt="Modern packaging design for organic skincare product, clean aesthetic, white background",
        style="realistic_image",
        size=1024,
        n_images=3,  # Generate 3 variations
        text_config={
            "content": "ORGANIC\nSKINCARE",
            "font": "modern_sans",
            "color": "#2C3E50",
            "position": "center"
        }
    )
    
    # Example 5: Icon set generation (vector)
    print("\nExample 5: Icon Set Generation")
    icon_themes = ["home", "settings", "profile", "notifications", "messages"]
    
    for icon in icon_themes:
        icon_prompt = f"Simple {icon} icon, minimalist line art style, monochrome black"
        icon_image = generate_image_recraft(
            prompt=icon_prompt,
            style="vector_illustration",
            size="512x512",
            output_format="svg"
        )
    
    # Example 6: Brand assets with consistent style
    print("\nExample 6: Consistent Brand Assets")
    brand_assets = generate_image_recraft_api(
        prompt="Corporate brand pattern with geometric shapes, professional aesthetic, navy blue and gold",
        style="digital_illustration",
        size=1024,
        n_images=4  # Generate 4 variations for consistency testing
    )
    
    print("\nAll design assets generated successfully!")
    print(f"Total cost (estimated): ~${len(social_prompts) * 0.04 + len(icon_themes) * 0.08 + 4 * 0.04:.2f}")
    print("Raster: $0.04/image, Vector: $0.08/image")

Code Example: Fal.ai Integration with Advanced Features

Fal.ai provides an alternative cloud endpoint for Recraft V3 with additional features like real-time streaming and batch processing optimization. This example demonstrates advanced integration patterns for production design workflows.

import fal_client
import os
import requests
from pathlib import Path
import time
from concurrent.futures import ThreadPoolExecutor, as_completed

# Fal.ai Configuration
fal_client.api_key = os.environ.get("FAL_KEY", "your_fal_key_here")

def generate_image_fal(prompt, style="realistic_image", image_size="square"):
    """
    Generate images with Recraft V3 via Fal.ai with real-time progress streaming
    
    Args:
        prompt: Text description
        style: Visual style (realistic_image, digital_illustration, vector_illustration)
        image_size: Preset size (square, landscape_4_3, portrait_4_3, etc.)
    
    Returns:
        Path to downloaded image
    """
    try:
        print(f"Generating with Recraft V3 via Fal.ai...")
        print(f"Prompt: {prompt[:80]}...")
        
        # Subscribe with real-time progress updates
        def on_queue_update(update):
            if isinstance(update, fal_client.InProgress):
                for log in update.logs:
                    print(f"[Progress] {log['message']}")
        
        result = fal_client.subscribe(
            "fal-ai/recraft-v3/text-to-image",
            arguments={
                "prompt": prompt,
                "style": style,
                "image_size": image_size,
                "quality": "high"
            },
            with_logs=True,
            on_queue_update=on_queue_update
        )
        
        # Download image
        image_url = result["images"][0]["url"]
        img_response = requests.get(image_url)
        img_response.raise_for_status()
        
        output_path = Path(f"recraft_fal_{int(time.time())}.png")
        with open(output_path, "wb") as f:
            f.write(img_response.content)
        
        print(f"Image saved to: {output_path}")
        print(f"Generation time: {result.get('timings', {}).get('inference', 'N/A')}ms")
        
        return output_path
        
    except Exception as e:
        print(f"Fal.ai error: {e}")
        raise

# Advanced: Batch processing with parallel execution
def batch_generate_designs(prompts, style="realistic_image", max_workers=5):
    """
    Generate multiple design assets in parallel for maximum throughput
    
    Args:
        prompts: List of prompt dictionaries with 'text' and optional 'style'
        style: Default style if not specified in prompt
        max_workers: Number of parallel requests
    
    Returns:
        List of results with success status and file paths
    """
    print(f"\nBatch generating {len(prompts)} designs with {max_workers} parallel workers...")
    
    results = []
    start_time = time.time()
    
    def process_prompt(idx, prompt_config):
        try:
            prompt_text = prompt_config.get("text", prompt_config)
            prompt_style = prompt_config.get("style", style)
            image_size = prompt_config.get("size", "square")
            
            print(f"\n[Worker {idx+1}] Starting: {prompt_text[:50]}...")
            
            image_path = generate_image_fal(
                prompt=prompt_text,
                style=prompt_style,
                image_size=image_size
            )
            
            return {
                "index": idx,
                "prompt": prompt_text,
                "path": image_path,
                "success": True
            }
        except Exception as e:
            print(f"[Worker {idx+1}] Failed: {e}")
            return {
                "index": idx,
                "prompt": prompt_config.get("text", prompt_config),
                "error": str(e),
                "success": False
            }
    
    # Execute in parallel
    with ThreadPoolExecutor(max_workers=max_workers) as executor:
        futures = {
            executor.submit(process_prompt, idx, prompt): idx 
            for idx, prompt in enumerate(prompts)
        }
        
        for future in as_completed(futures):
            result = future.result()
            results.append(result)
            
            completed = len(results)
            print(f"\n[Batch Progress] {completed}/{len(prompts)} completed")
    
    # Sort results by original index
    results.sort(key=lambda x: x["index"])
    
    total_time = time.time() - start_time
    successful = sum(1 for r in results if r["success"])
    
    print(f"\n=== Batch Complete ===")
    print(f"Total: {len(prompts)} | Successful: {successful} | Failed: {len(prompts) - successful}")
    print(f"Total time: {total_time:.2f}s | Avg per image: {total_time/len(prompts):.2f}s")
    print(f"With parallelization: ~{total_time/max_workers:.2f}s effective time per image")
    
    return results

# Real-world use case: E-commerce product catalog
if __name__ == "__main__":
    # Single high-quality generation
    print("Example 1: Hero Image Generation")
    hero_image = generate_image_fal(
        prompt="Luxury watch product photography, studio lighting, marble surface, premium aesthetic, 8k quality",
        style="realistic_image",
        image_size="landscape_16_9"
    )
    
    # Batch generation for product catalog
    print("\nExample 2: Product Catalog Batch Generation")
    product_prompts = [
        {"text": "Modern wireless earbuds in charging case, white background, product photography", "style": "realistic_image"},
        {"text": "Minimalist desk lamp with adjustable arm, studio lighting, clean aesthetic", "style": "realistic_image"},
        {"text": "Leather laptop bag, professional product shot, brown leather texture", "style": "realistic_image"},
        {"text": "Stainless steel water bottle, outdoor lifestyle setting", "style": "realistic_image"},
        {"text": "Ergonomic office chair, modern design, gray fabric", "style": "realistic_image"},
        {"text": "Smartphone charging dock, tech product photography", "style": "realistic_image"},
        {"text": "Running shoes, dynamic angle, athletic aesthetic", "style": "realistic_image"},
        {"text": "Coffee maker machine, kitchen product photography", "style": "realistic_image"}
    ]
    
    catalog_results = batch_generate_designs(product_prompts, max_workers=4)
    
    # Generate design variations
    print("\nExample 3: Design Variations")
    variations_prompts = [
        {"text": "App icon with mountain theme, minimalist, blue gradient", "style": "vector_illustration", "size": "square"},
        {"text": "App icon with mountain theme, modern, geometric shapes", "style": "vector_illustration", "size": "square"},
        {"text": "App icon with mountain theme, abstract, bold colors", "style": "vector_illustration", "size": "square"}
    ]
    
    variation_results = batch_generate_designs(variations_prompts, max_workers=3)
    
    # Calculate costs
    total_raster = sum(1 for p in product_prompts if p.get("style") != "vector_illustration")
    total_vector = sum(1 for p in variations_prompts if p.get("style") == "vector_illustration")
    estimated_cost = (total_raster * 0.04) + (total_vector * 0.08)
    
    print(f"\n=== Summary ===")
    print(f"Raster images: {total_raster} x $0.04 = ${total_raster * 0.04:.2f}")
    print(f"Vector images: {total_vector} x $0.08 = ${total_vector * 0.08:.2f}")
    print(f"Total estimated cost: ${estimated_cost:.2f}")
    print(f"\nAll design assets ready for deployment!")

Professional Integration Services by 21medien

Implementing Recraft V3 for design-focused applications requires expertise in typography systems, vector graphics workflows, and brand consistency automation. 21medien offers specialized integration services to help design teams and businesses leverage Recraft V3's unique text and design capabilities.

Our services include: Design System Integration for connecting Recraft V3 with your brand guidelines, style guides, and asset management systems, Text-to-Design Automation for generating marketing materials, social media graphics, and product mockups with precise text placement, Vector Workflow Optimization for scalable logo generation, icon sets, and print-ready graphics with SVG export pipelines, Brand Consistency Tools for maintaining visual identity across thousands of generated assets with automated quality control, Batch Processing Infrastructure for high-volume design asset generation with parallel processing and cost optimization, Custom API Development for seamless integration with your design tools, content management systems, and marketing automation platforms, and Prompt Engineering Consultation to achieve pixel-perfect text placement, consistent styling, and professional design quality.

Whether you need an automated social media graphics pipeline, scalable brand asset generation, or custom integration with your design workflow, our team of AI engineers and design technology specialists understands the unique requirements of design-focused AI. Schedule a free consultation call through our contact page to discuss your design automation needs and explore how Recraft V3's industry-leading text generation capabilities can scale your creative production.

Resources and Links

Official website: https://www.recraft.ai/ | Image Generator: https://www.recraft.ai/ai-image-generator | Blog: https://www.recraft.ai/blog | Launch Announcement: https://www.recraft.ai/blog/recraft-introduces-a-revolutionary-ai-model-that-thinks-in-design-language | API Documentation: https://www.recraft.ai/blog/discover-the-power-of-recrafts-image-generation-api | Replicate: https://replicate.com/recraft-ai/recraft-v3 | Fal: https://fal.ai/models/fal-ai/recraft/v3/text-to-image