You are probably paying 3-5x more than you need to for LLM API calls. Not because the models are expensive — because you are using the wrong model for most tasks.
The Math
- Claude Sonnet: $15/million tokens
- DeepSeek-V3: $1.80/million tokens
- MiniMax M2.7: $0 (free, unlimited)
If 60% of your tasks are simple enough for the cheap model, you are overpaying by 60% * ($15 - $1.80) = $7.92 per million tokens.
At 100+ requests per day, that adds up to $100+/month in waste.
What Counts as Simple
- File reads and grep — any model handles this
- Formatting and lint fixes — no reasoning needed
- Test boilerplate — template-based generation
- Simple refactors (rename, extract) — straightforward transforms
- Basic Q&A — lookup, not reasoning
What Actually Needs the Expensive Model
- Multi-file architecture decisions
- Complex async debugging
- Security analysis
- System design
The Fix
Route by task type. Cheap model for simple ops, premium for complex ones.
TeamoRouter does this automatically. teamo-balanced mode auto-selects. teamo-free gives unlimited MiniMax for the simplest tasks.
Discord for cost optimization strategies.
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