Gemini 2.5 Pro vs GPT-4.1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Gemini 2.5 Pro | GPT-4.1 |
|---|---|---|
| Provider | OpenAI | |
| Input Price (1M) | $1.25 | $2.00 |
| Output Price (1M) | $10.00 | $8.00 |
| Context Window | 1,000,000 | 1,000,000 |
Verdict
Gemini 2.5 Pro costs $1.25 per 1M input tokens and $10.00 per 1M output tokens. GPT-4.1 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens. Gemini 2.5 Pro is 38% cheaper on input tokens than GPT-4.1. For output tokens, GPT-4.1 is the more affordable option at $8.00/1M vs $10.00.
On context window, Gemini 2.5 Pro supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Gemini 2.5 Pro
- ✓ You need the lowest input token cost ($ 1.25/1M)
- ✓ You are already integrated with Google
When to choose GPT-4.1
- ✓ Your workload is output-heavy — GPT-4.1 generates text cheaper
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Gemini 2.5 Pro cheaper than GPT-4.1? ▼
Gemini 2.5 Pro is cheaper on input tokens at $1.25/1M vs $2.00/1M for GPT-4.1 — a 38% saving.
What is the context window of Gemini 2.5 Pro vs GPT-4.1? ▼
Gemini 2.5 Pro has a 1,000,000-token context window. GPT-4.1 has a 1,000,000-token context window. Gemini 2.5 Pro supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Gemini 2.5 Pro or GPT-4.1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Gemini 2.5 Pro is the cheaper option. For maximum context length, Gemini 2.5 Pro supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.