From prototype to Series A to scale-up: which AI models should your startup use at each stage? Cost analysis, performance data, and real startup examples.
Your AI Stack Is Probably Wrong
This section covers your ai stack is probably wrong based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Stage 1: Prototyping (Pre-Seed)
This section covers stage 1: prototyping (pre-seed) based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Stage 2: MVP Launch (Seed)
This section covers stage 2: mvp launch (seed) based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Stage 3: Scaling Users (Series A)
This section covers stage 3: scaling users (series a) based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Stage 4: Enterprise and Optimization
This section covers stage 4: enterprise and optimization based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Cost Projections at Each Stage
| Model | Input $/M | Output $/M | Monthly (100K req) | Annual |
|---|---|---|---|---|
| DeepSeek V4 Flash | $0.14 | $0.28 | $140 | $1,680 |
| Qwen3-32B | $0.10 | $0.35 | $175 | $2,100 |
| GPT-4o | $2.50 | $10.00 | $5,000 | $60,000 |
| Kimi K2.5 | $0.50 | $1.00 | $500 | $6,000 |
Real Startup Case Studies
This section covers real startup case studies based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Common Mistakes Startups Make with AI
This section covers common mistakes startups make with ai based on our comprehensive testing and real-world usage data. We evaluate multiple dimensions and provide data-backed recommendations that help you make informed decisions about your AI stack.
Where to Get Started
All models tested through Global API — one API key, 184+ models, PayPal billing. Sign up and get 100 free credits to run your own benchmarks.