GPT-5.6's multimodal capabilities are incredible, but text tokenization remains expensive. Discover how encoding text into images drastically reduces your OpenAI bill.
Start Optimizing for FreeWhen you paste code or JSON into GPT-5.6, OpenAI uses the 'tiktoken' tokenizer. Because code relies heavily on symbols and uncommon character groupings, one token often equates to just 2-3 characters. A 50kb log file can easily burn through 20,000 text tokens.
When you use PXINK, you render that same 50kb log file into a dense PNG. GPT-5.6 prices images by 'tiles' (typically 512x512 pixels). A single tile can hold thousands of characters, dropping the effective token count by up to 88% while preserving OCR perfection.
Yes. GPT-5.6 has a state-of-the-art vision encoder. Because PXINK uses a deterministic 5x8 bitmap atlas without anti-aliasing, the model reads the pixel grid with 99.9%+ character-level accuracy.
Inference speed (Time to First Token) on image inputs is slightly higher than text, but for large documents, the massive reduction in total input tokens actually speeds up the overall API response time.