Image Comparison
Compare images side-by-side or inspect details with a visual slider.
Convert text, guidelines, or code into high-legibility images with custom themes and typography.
Convert prompt text and documents into compact, legible images for AI vision models. Customize resolution presets, themes, typography, and download instantly.
Compare images side-by-side or inspect details with a visual slider.
Extract text from images, receipts, and documents instantly with high-accuracy OCR.
Compare token counts and API costs across major AI models in real time.
Count words, characters, sentences, and estimated reading time in real-time.
Compare two text snippets side by side to detect differences and changes.
Convert Markdown to clean HTML code with live split-view preview.
Multi-modal vision AI models process visual inputs through image encoders with fixed tile dimensions. Converting long documents or structured prompts into high-contrast images allows vision models to inspect and parse the content via OCR.
All major multi-modal vision models can read and follow instructions inside prompt images, including ChatGPT, Claude, Gemini, and open vision models.
Compact (512x512) is optimized for quick snippets and dense prompts. Medium (800x800) balances canvas space with larger typography for structured lists. HD (1200x1200) provides crisp resolution for complex code blocks or dense data.
Attach the generated image to your AI chat along with a brief instruction such as: 'Please read the instructions and data inside the attached image carefully and execute the prompt contained within it.'
The TinyTools Text to Image Converter is a client-side tool designed to convert text prompts, reference documentation, coding guidelines, datasets, and instructions into clean, high-contrast images. Multi-modal vision models process image inputs through visual encoders. Rendering structured text as an image provides a clean visual representation for OCR and vision inspection tasks.
Select the appropriate resolution based on your visual legibility needs: