The cost comparison that matters
The economics of edge AI vs cloud AI depend on exactly one variable more than any other: scale. At low query volumes, cloud wins on cost. At enterprise volumes, edge wins overwhelmingly. The crossover point is lower than most people think.
Let us build the cost model from first principles, using real numbers.
Cloud API costs (2026 pricing, approximate):
| Provider/Model | Input (per 1M tokens) | Output (per 1M tokens) | Typical cost per query* |
|---|---|---|---|
| OpenAI GPT-4o | $2.50 | $10.00 | $0.005-0.015 |
| OpenAI GPT-4.1 | $2.00 | $8.00 | $0.004-0.012 |
| Anthropic Claude Sonnet 4 | $3.00 | $15.00 | $0.006-0.020 |
| Anthropic Claude Opus 4 | $15.00 | $75.00 | $0.030-0.100 |
| Google Gemini 2.5 Pro | $2.50 | $15.00 | $0.006-0.020 |
*Assumes average query: 500 input tokens, 300 output tokens
Edge infrastructure costs (one-time hardware + ongoing):
| Configuration | Hardware cost | Annual operating cost | Capacity |
|---|---|---|---|
| Single RTX 4090 (desktop) | $2,000 | $800 (power) | 5K-15K queries/day |
| Single L40S (server) | $9,000 | $3,000 (power + admin) | 20K-50K queries/day |
| 2x A100 40GB (production) | $24,000 | $8,000 (power + admin) | 50K-200K queries/day |
| 4x A100 80GB (high-scale) | $70,000 | $15,000 (power + admin) | 200K-500K queries/day |
The edge marginal cost per query is effectively $0 once the infrastructure is in place. You are paying for capacity, not usage.
