LLM Cost Optimization with TOON
Cut your AI application costs by 30-60% without sacrificing quality or functionality.
Understanding LLM Costs
Current Pricing (2025)
| Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|
| GPT-4 Turbo | $10.00 | $30.00 |
| GPT-3.5 Turbo | $0.50 | $1.50 |
| Claude Opus | $15.00 | $75.00 |
| Claude Sonnet | $3.00 | $15.00 |
Potential Savings Calculator
Example Scenario:
• 100,000 API calls per month
• Average 1,000 tokens per request (input)
• Using GPT-4 Turbo ($10/1M tokens input)
• 500 tokens of structured data per request
Save $300/month = $3,600/year
Cost Optimization Strategies
1️⃣Convert Structured Data to TOON
Replace JSON arrays and objects with TOON format in your prompts. Focus on data-heavy sections like product lists, user data, or API responses.
2️⃣Optimize Prompt Engineering
Combine TOON with concise instructions. Remove unnecessary examples or explanations once the model understands the format.
3️⃣Batch Similar Requests
Process multiple items in one request using TOON's tabular format. Instead of 10 separate calls, send one with a 10-row TOON table.
4️⃣Cache Common Data
Use TOON for reference data that appears in multiple prompts. Smaller token footprint means more efficient caching.
5️⃣Monitor and Iterate
Track token usage before and after TOON adoption. Use analytics to identify high-token prompts for conversion.
Implementation ROI
Week 1: Setup & Testing
Integrate TOON library, convert test datasets, verify accuracy
Week 2-3: Gradual Rollout
Deploy to 25%, then 50% of traffic, monitor performance
Month 1: Full Deployment
100% traffic on TOON, start seeing 30-60% cost reduction
Month 3: Optimization
Fine-tune based on analytics, maximize savings
📊 Real Case Study
SaaS Company - Customer Support Automation
- • 500,000 support queries/month processed by GPT-4
- • Average 800 tokens per query with customer data
- • Switched to TOON for customer profiles and order history
Before: $4,000/month
After: $2,400/month
Savings: $1,600/month ($19,200/year)