IllustriousNXT_XL_v2.0a by klaabu
klaabu_IllustriousNXT_XL_v2.0a is a fine-tuned evolution of the Illustrious anime model, built for creators who demand sharp detail, strong prompt control, and versatile style coverage. This version improves overall fidelity, boosts knowledge of artist styles and art genres, and maintains full text encoder strength — giving you responsive, high-impact results with both tag-based and natural language prompts.
🎯 Core Features
• Fine-Tuned Base: Improved ???????, lighting, and output consistency
• Style Awareness: Enhanced recognition of popular artists and art styles
• Prompt Flexibility: Accepts Danbooru tags and natural language equally well
• LoRA Friendly: Fully supports LoRAs for characters, bodies, faces, and aesthetics
• Encoder: Retains full text encoder with updated token awareness (trained up to 2025)
• Resolution: Native support for 512×512 to 1536×1536+
🛠️ Recommended Settings
• Sampler: Euler A or DPM++ 2M SDE, Schedule type: SGM Uniform
• CFG Scale: 3 – 7
• Steps: 25 – 35
• VAE: Optional
🧷 Suggested Positive Tags
(masterpiece, best_quality, ultra_detailed, expressive eyes, clean shading)
🚫 Suggested Negative Tags
(worst_quality, jpeg artifacts, watermark, child, blurry, malformed hands)
Safety Tip:
Use strong negative prompts to avoid unwanted content and keep generations clean.
🧪 Best Use Cases
• High-quality character and scene illustrations
• Art-style experiments and aesthetic LoRA testing
• Visual novel assets, covers, and expressive portraits
Leave feedback, share results, or tag me with your outputs — I'm continuing to refine and improve based on what the community creates.
Description
IllustriousNXT_XL_v2.0a by klaabu
klaabu_IllustriousNXT_XL_v2.0a is a fine-tuned evolution of the Illustrious anime model, built for creators who demand sharp detail, strong prompt control, and versatile style coverage. This version improves overall fidelity, boosts knowledge of artist styles and art genres, and maintains full text encoder strength — giving you responsive, high-impact results with both tag-based and natural language prompts.
🎯 Core Features
• Fine-Tuned Base: Improved ???????, lighting, and output consistency
• Style Awareness: Enhanced recognition of popular artists and art styles
• Prompt Flexibility: Accepts Danbooru tags and natural language equally well
• LoRA Friendly: Fully supports LoRAs for characters, bodies, faces, and aesthetics
• Encoder: Retains full text encoder with updated token awareness (trained up to 2025)
• Resolution: Native support for 512×512 to 1536×1536+
🛠️ Recommended Settings
• Sampler: Euler A or DPM++ 2M SDE SGM Uniform
• CFG Scale: 3 – 7
• Steps: 25 – 35
• VAE: Optional
🧷 Suggested Positive Tags
(masterpiece, best_quality, ultra_detailed, expressive eyes, clean shading)
🚫 Suggested Negative Tags
(worst_quality, jpeg artifacts, watermark, child, blurry, malformed hands)
Safety Tip:
Use strong negative prompts to avoid unwanted content and keep generations clean.
🧪 Best Use Cases
• Anime-realism hybrid art
• High-quality character and scene illustrations
• Art-style experiments and aesthetic LoRA testing
• Visual novel assets, covers, and expressive portraits
Leave feedback, share results, or tag me with your outputs — I'm continuing to refine and improve based on what the community creates.