Current Pricing Landscape
As of mid-2026, the three dominant multimodal LLM providers charge significantly different rates. Claude Sonnet 4.6: $3/M input tokens. GPT-5.6: $2.50/M input tokens. Gemini 3.1 Pro: $1.25/M input tokens. These prices apply to text tokens. Image token pricing differs across all three.
Image Token Pricing Differences
Claude charges image tokens at the same rate as text tokens but uses fewer of them per image. GPT-5.6 offers a flat 85-token rate in low-detail mode. Gemini processes images through its own tokenizer at roughly 1,100 tokens per 1000×720 page. The net effect: visual encoding saves money across all three, but the exact percentage varies.
Cost Per 100K Characters: Text vs. Image
Processing 100,000 characters as text costs: Claude $0.085, GPT-5.6 $0.071, Gemini $0.036. The same content as dense PNGs costs: Claude $0.010, GPT-5.6 $0.008, Gemini $0.004. Savings range from 88% (Claude) to 89% (Gemini).
Choosing the Right Provider
For maximum quality: Claude Sonnet 4.6 remains the gold standard for code analysis and nuanced reasoning. For maximum affordability: Gemini 3.1 Pro offers strong multimodal performance at half the cost. For ecosystem compatibility: GPT-5.6 integrates seamlessly with the broader OpenAI platform.
The Provider-Agnostic Advantage of Visual Encoding
Because dense PNGs are standard image files, you can switch providers without changing your encoding pipeline. Generate your images once, then route them to whichever provider offers the best price-to-performance ratio for your specific use case.
Frequently Asked Questions
Conclusion
Visual token encoding is a practical, immediately deployable optimization that works with your existing AI stack. Whether you are a developer building pipelines or a founder managing API budgets, the ~88% input cost reduction compounds into real savings that improve your margins and extend your runway.
Ready to try it? Open PXINK and drop a file to see your savings instantly.