Platform Guide
Platform Guide
Section titled “Platform Guide”Each prompt is provided in four platform-specific variants. Understanding their strengths will help you get the best results.
🔵 Nano Banana 2 (Featured — Best Overall Quality)
Section titled “🔵 Nano Banana 2 (Featured — Best Overall Quality)”Nano Banana 2 (powered by Gemini 3.1 Flash Image) is a major upgrade over the original. Treat it as a full-featured creative engine, not a quick-filter tool.
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Style: Detailed, structured natural language. Front-load the asset type and primary subject, then layer in style, lighting, and composition details.
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Strengths: Combines pro-model quality with flash-model speed. Supports multi-turn conversational refinement, search grounding (reference real-world subjects by name), accurate text rendering, character consistency (up to 5 characters), and output up to 4K resolution.
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Why It’s Featured: NB2 consistently produces the most detailed, accurate, and stylistically faithful results across all 57 styles in this library. Its conversational refinement loop means you can iterate toward perfection without re-writing your entire prompt.
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Key Tips:
Tip Details Be specific, not vague NB2’s reasoning engine rewards precise descriptors for textures, colors, and lighting over generic adjectives Front-load important details Place the asset type and primary subject at the beginning of your prompt Specify aspect ratios Explicitly state the format: 16:9for wallpapers,3:4for Instagram,9:16for stories,1:1for profile picturesIterate conversationally Refine with follow-ups: “Change the palette to warmer tones,” “Move the subject left,” “Add more texture to the background” Leverage search grounding For real-world subjects, ask the model to reference accurate imagery: “Use image search to find accurate reference for [specific subject]“ Use positive framing Instead of “no cars,” describe the scene you do want: “empty, deserted street” Specify camera/lens For photographic styles, include lens (85mm, 35mm, macro), aperture (f/1.8, f/8), and camera angle (low, eye-level, bird’s eye) Name your lighting Use specific lighting terms: “Rembrandt lighting,” “golden hour,” “tungsten warm glow,” “volumetric fog”
ChatGPT (GPT-4o Image Generation)
Section titled “ChatGPT (GPT-4o Image Generation)”Replaces the standalone DALL-E 3 model, which is deprecated as of May 2026.
- Style: Fully conversational, natural language. Describe your scene as if briefing an artist.
- Strengths: Excellent scene comprehension, precise spatial relationships, and iterative refinement through follow-up messages.
- Tips: Be specific about subject placement, lighting direction, and mood. You can assign it a persona (e.g., “Act as a professional product photographer”) for higher fidelity. Use follow-up messages to adjust individual elements without re-describing the whole scene.
Midjourney (V7)
Section titled “Midjourney (V7)”V7 is the current default model. Parameters like
--v 6.0are no longer needed.
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Style: Natural language with parameters appended at the end. V7 has moved away from keyword stuffing toward descriptive sentences.
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Key Parameters:
Parameter Purpose Example --arAspect ratio --ar 16:9,--ar 4:5--sStylization (0–1000). Low = literal, high = artistic --s 250--noExclude elements (replaces negative prompts) --no text, blur--crefCharacter reference — maintains identity across images --cref [URL]--srefStyle reference — applies the aesthetic of a reference image --sref [URL]--iwImage weight for reference influence (0–2) --iw 1.5--chaosVariation in initial grid (0–100) --chaos 30 -
Tips: Place the most important visual information first. Use
--nijifor anime and illustration styles.
Stable Diffusion (SDXL / SD 3.5)
Section titled “Stable Diffusion (SDXL / SD 3.5)”- Style: Supports both keyword tags and natural language. Modern models (SDXL, SD 3.5) work best with descriptive sentences, structured as Subject → Action → Environment → Style/Lighting.
- Negative Prompts: Use sparingly and only for specific unwanted elements. Bloated negative prompt lists degrade output quality on modern models. Try generating without negatives first, then add targeted exclusions as needed.
- Tips: Avoid over-weighting (e.g.,
(keyword:1.5)) — use it to nudge, not force. Ensure your resolution matches the model’s native aspect ratio.