Gemini 2.x Pro vs GPT-4o: cost & margin
Gemini 2.x Pro (Google) and GPT-4o (OpenAI) sit at different price points. At a typical 500k/150k token mix per customer, Gemini 2.x Pro is cheaper ($2.13 vs $2.75 per customer), and GPT-4o has the lower output-token price — the part that usually drives an AI SaaS bill.
| Gemini 2.x Pro | GPT-4o | |
|---|---|---|
| Input $/Mtok | $1.25 | $2.5 |
| Output $/Mtok | $10 | $10 |
| Cost / customer (typical) | $2.13 | $2.75 |
| Margin at $49/mo | 95.7% | 94.4% |
Cost per customer as usage grows
Monthly LLM cost per customer at four usage levels — the gap widens the more your customers use.
| Usage / mo | Gemini 2.x Pro | GPT-4o |
|---|---|---|
| Light | $0.43 | $0.55 |
| Typical | $2.13 | $2.75 |
| Heavy | $8.50 | $11.00 |
| Power user | $35.00 | $45.00 |
Which should you pick?
Gemini 2.x Pro
Best for context-heavy, retrieval-style features (RAG, document analysis): cheaper input lets you feed large prompts on a flat price.
GPT-4o
Worth it when its quality justifies the higher token cost — price your plans to cover the difference.
Verdict: at a typical token mix, Gemini 2.x Pro is the cheaper choice per customer. Heavier or output-heavy workloads can change the picture — check yours below.
FAQ
- Which is cheaper, Gemini 2.x Pro or GPT-4o?
- At a typical 500k / 150k token mix, Gemini 2.x Pro is cheaper — $2.13 vs $2.75 per customer per month, a $0.62 gap that widens as usage grows.
- Does GPT-4o ever make more sense than Gemini 2.x Pro?
- Yes — token price isn't everything. If GPT-4o needs fewer retries or shorter outputs to finish the job, or its quality lifts conversion, it can be the better margin call despite the higher per-token price. Model it on your own usage.
Per-model details
Other comparisons