I've consulted for startups burning $200/month on AI and enterprises spending $200,000. Here's what nobody tells you: the startup paying $200 is often getting better results than the enterprise paying 1,000x more.
Cost at Different Scales
| Stage | Funding | Tokens/Month | GPT-4o Cost | Smart Routing | With V4 Flash |
|---|---|---|---|---|---|
| Bootstrapped MVP | $0 | 5M | $50 | $1.25 | $1.25 |
| Seed-stage | $500K | 50M | $500 | $12.50 | $12.50 |
| Series A | $5M | 500M | $5,000 | $125 | $125 |
| Series B | $20M | 5B | $50,000 | $1,250 | $1,250 |
| Enterprise | N/A | 50B | $500,000 | $12,500 | $12,500 |
The Key Insight
The cost difference between GPT-4o and DeepSeek V4 Flash is so massive that at every scale, the savings are transformative. At bootstrapped scale, it's the difference between "can I afford this?" and "this is pocket change." At enterprise scale, it's the difference between a $500K line item and a $12.5K line item — literally headcount decisions.
My recommendation for every stage:
# Production config that works at any scale
MODEL_TIERS = {
"free_tier": "Qwen/Qwen3-8B", # $0.01/M
"standard": "deepseek-ai/DeepSeek-V4-Flash", # $0.25/M
"premium": "deepseek-reasoner", # $2.50/M
"enterprise": "Pro/DeepSeek-V3.2", # Dedicated instance
}Start with standard tier. Upgrade as you grow. Don't over-engineer early. Access all models through Global API.