/tags/text-to-image/ Recent content in Text-to-Image on AI Prompt Toolkit Hugo en-us Fri, 12 Jun 2026 00:00:00 +0000 /prompts/ideogram-4-0-master-prompts/ Fri, 12 Jun 2026 00:00:00 +0000 /prompts/ideogram-4-0-master-prompts/ <h2 id="ideogram-40-optimization-guide">Ideogram 4.0 Optimization Guide</h2> <p>Ideogram 4.0 (June 2026) is a <strong>9.3B parameter Diffusion Transformer (DiT)</strong> trained from scratch with flow-matching — and it ships <strong>open weights</strong> for the first time. It ranks <strong>#2 overall</strong> on image generation leaderboards, behind only GPT Image 2.0, and is the <strong>#1 open-weight model</strong> on Design Arena and LMArena.</p> <h3 id="key-strengths">Key Strengths</h3> <ul> <li><strong>Text-Rich Layouts</strong>: Posters, UI mockups, labelled diagrams — text renders clean without garbled characters</li> <li><strong>Bounding Box Control</strong>: JSON-style <code>bbox</code> coordinates for pixel-precise element placement</li> <li><strong>Color Palette Adherence</strong>: Explicit hex color arrays produce consistent brand outputs</li> <li><strong>2K Native Resolution</strong>: Trained at 2048×2048 — always specify &ldquo;2K&rdquo; for optimal quality</li> </ul> <h3 id="prompt-structure">Prompt Structure</h3> <p>Ideogram 4.0 responds best to <strong>JSON-structured prompts</strong> with explicit spatial coordinates. Unlike diffusion models that benefit from verbose natural language, Ideogram&rsquo;s DiT architecture prefers structured parameterization:</p>