The Basic Formula
Cost = (input_tokens × input_price + output_tokens × output_price) / 1,000,000. For Claude Sonnet 4.6: input_price = $3, output_price = $15. A request with 10,000 input tokens and 2,000 output tokens costs: (10,000 × $3 + 2,000 × $15) / 1,000,000 = $0.06.
Estimating Input Tokens From Text
Rule of thumb: divide character count by 3.5 for English prose, 3.0 for code, 2.5 for JSON, and 2.0 for minified code. These ratios are approximations — use your provider's tokenizer library for exact counts.
Estimating Image Tokens
Count the 512×512 tiles in your image. Tiles = ceil(width/512) × ceil(height/512). Multiply by 1,334 (Claude) or 170 (GPT-5.6 high detail). For pxpipe pages at 1000×720: 2×2 tiles = 5,336 Claude tokens.
PXINK's Built-In Calculator
PXINK shows both text tokens and image tokens after rendering. The 'Saved' percentage is calculated in real-time. Use this to estimate costs before committing to API calls. Render your payload, check the numbers, then decide whether visual encoding is worth it for your specific use case.
Monthly Cost Projections
Multiply your per-query cost by expected daily volume and 30 days. Factor in both input and output tokens. For most applications, input tokens dominate the cost — which is exactly where visual encoding delivers its savings.
Quick Cost Estimator Script
def estimate_cost(
char_count: int,
content_type: str = "code",
use_visual_encoding: bool = False,
provider: str = "claude_sonnet",
output_tokens: int = 2000
) -> dict:
"""Estimate API cost for a given payload."""
chars_per_token = {"prose": 3.5, "code": 3.0, "json": 2.5, "minified": 2.0}
input_prices = {"claude_sonnet": 3.0, "gpt4o": 2.5, "gemini_pro": 1.25}
output_prices = {"claude_sonnet": 15.0, "gpt4o": 10.0, "gemini_pro": 5.0}
text_tokens = char_count / chars_per_token.get(content_type, 3.0)
if use_visual_encoding:
chars_per_page = 25000
pages = max(1, char_count / chars_per_page)
input_tokens = pages * 5336 # 2x2 tiles per page
else:
input_tokens = text_tokens
price = input_prices[provider]
cost = (input_tokens * price + output_tokens * output_prices[provider]) / 1_000_000
savings = (1 - input_tokens / text_tokens) * 100 if use_visual_encoding else 0
return {"input_tokens": int(input_tokens), "cost": f"${cost:.4f}", "savings": f"{savings:.1f}%"}
print(estimate_cost(100_000, "code", use_visual_encoding=False))
print(estimate_cost(100_000, "code", use_visual_encoding=True))
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.