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Lykon

Absolute Reality

Released

2023-08-03

Family

Stable Diffusion 1

Type

Fine-Tuned Model

Downloads

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Model Checkpoint

FP16 · 1.9 GB · absolute-reality.fp16.safetensors

Inpainting Model

FP16 · 3.9 GB · absolute-reality-inpainting.fp32.safetensors

Model Report

Overview

Absolute Reality is a photorealistic image generation model built on the Stable Diffusion 1.5 framework, specifically designed to produce high-fidelity, realistic digital images. Developed by Lykon and first released on August 3, 2023, Absolute Reality distinguishes itself from artistic or multi-purpose variants by focusing on precise replication of photographic style and detail, especially in portraiture and simulated photography tasks. The model is available in both standard and inpainting versions, as well as an LCM (Latent Consistency Model) variant, offering flexibility for differing generative tasks. Ongoing updates, most recently reflected in version 1.8.1 as of March 22, 2025, introduce refinements in realism and detail handling, particularly for facial features and textures. The underlying technology, data, and community-use strategies situate Absolute Reality as a relevant checkpoint in the playground of photorealistic text-to-image synthesis models.

Highly detailed photorealistic AI portrait by Absolute Reality, showing a young woman in reflective medieval armor

Figure 1. An AI-generated photorealistic portrait created with Absolute Reality, emphasizing intricate metallic textures and naturalistic lighting. Example prompt: 'young woman in medieval armor, reflective surfaces, detailed background'.

Technical Foundations

Absolute Reality is built upon the Stable Diffusion 1.5 architecture, inheriting the robust latent diffusion method and optimization pipeline recognized for balancing image quality with computational efficiency. The model checkpoint is distributed in SafeTensor format, ensuring secure model loading and reproducibility within compatible diffusion platforms. As a "checkpoint trained" model, Absolute Reality employs fine-tuning on a diverse dataset with an emphasis on realism and photographic authenticity.

During its development, initial training was conducted alongside the creation of DreamShaper 6, but Absolute Reality diverged by targeting strictly photorealistic outcomes. The mixing process incorporated select photorealistic models and custom LoRA modules, such as an ISO noise LoRA, to simulate photographic grain and analog effects directly within the generative pipeline. Incremental updates have enhanced aspects such as eye rendering, skin realism, and overall image detail, reflecting community feedback and iterative optimization. Inpainting editions support detailed, context-aware modifications to specific regions of an image, while the LCM variant offers additional sampling efficiency.

Futuristic cyberpunk-style AI portrait showing a character with dramatic lighting

Figure 2. Photorealistic character output with a cyberpunk theme, generated by Absolute Reality. The model demonstrates nuanced handling of lighting and stylized attire. Prompt example: 'cyberpunk portrait, neon city, dramatic light'.

Model Features and Prompting Strategies

Absolute Reality is optimized for simple prompt structures that center on real-world photographic concepts. The model demonstrates strong adherence to photorealism, with its output often described as indistinguishable from conventional digital photography. Photorealistic results are obtainable with minimal prompt engineering, while overly complex prompts may lead to diminished realism due to the base CLIP architecture's limitations—colloquially known as "CLIP bleeding."

Version 1.8.1 delivers sharper facial details, robust eye rendering, and nuanced skin tones across diverse ethnicities and complexions. Customization for attributes such as eye color, hairstyle, and references to cultural or celebrity features is supported, enabling tailored portrait synthesis. Integration with auxiliary tools like ADetailer enhances face clarity and detail when used with moderate denoising settings.

Inpainting support enables targeted area modifications, useful for iterative image editing or correction. The model also accommodates advanced configurations, including Highres.fix for upscaling and multi-step DPM++ SDE Karras-based sampling to augment sharpness and detail control.

Recommended operational parameters, designed through extensive user feedback, include a CFG scale between 4.5 and 10, DPM++ SDE Karras sampler, 25–30 sampling steps, CLIP Skip set to 2, and Highres.fix denoising strength of 0.45 paired with high-quality upscalers. Negative embeddings such as 'BadDream' or 'UnrealisticDream' further suppress non-photorealistic artifacts, aligning outputs closely with naturalistic imaging standards.

Photorealistic portrait of a young man in metallic futuristic armor, generated by Absolute Reality

Figure 3. A highly realistic AI-generated portrait demonstrating Absolute Reality's proficiency in skin texture and metallic material rendering. Prompt: 'male portrait, futuristic armor, cinematic lighting'.

Typical Applications and Use Cases

Absolute Reality is primarily utilized for generating hyperrealistic portraits, simulated photography, and landscape imagery where visual authenticity is essential. Its specialized training for nuanced facial synthesis makes it highly effective for character portraiture, both for individual and creative collective projects. Typical applications extend to generating digital models for media, pre-visualization in entertainment and design workflows, as well as the simulation of various photographic conditions—including analog effects via controlled noise or grain.

Image-to-image transfer workflows benefit from pairing Absolute Reality with more versatile, artistic checkpoints such as DreamShaper; initial artistic renders from DreamShaper 6 can be refined through img2img transfer with Absolute Reality to enhance realism. Dedicated inpainting versions allow for seamless, context-sensitive edits, making the model suitable for tasks in digital restoration or content-aware photo editing.

Limitations and Model Comparison

The focus on strict realism imposes trade-offs in flexibility compared to multi-purpose models like DreamShaper, which supports a broader spectrum of visual styles and higher compatibility with LoRA fine-tuning for non-photorealistic outputs. Absolute Reality is less suitable for overtly stylized or artistic genres and exhibits moderate adherence to elaborate prompt specifications. The built-in face restoration feature has received critical feedback for suboptimal results and is typically disabled in workflows.

While robust at producing realistic content, the model is constrained by the general safety and scope of its training data and relies on users to apply appropriate negative prompt embeddings and sampling configurations to avoid undesirable outputs or artifacts.

Licensing and Availability

Absolute Reality is distributed under the CreativeML Open RAIL-M license, with usage constrained to the terms stipulated by its creators and open-source community conventions. The model is publicly accessible for research, education, and non-commercial application.

External Resources

For further reference and practical usage guides, the following resources are recommended:

About Stable Diffusion 1: Stable Diffusion is an open-source text-to-image generative AI model that transforms textual adminDescriptions into corresponding images. Technologically, it employs a latent diffusion model architecture, enhancing computational efficiency by performing diffusion processes in a compressed latent space, which enables high-quality image generation with reduced resource requirements.

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