Gemini 2.5 Pro vs GPT-5 nano
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
Gemini 2.5 Pro
70.9Google · Mar 2025
Google's 2025 workhorse flagship — first mainstream thinking model with a 1M context, still widely deployed.
GPT-5 nano
OpenAI · Aug 2025
OpenAI's cheapest model — $0.05 per million input tokens — for latency-critical routing, autocomplete and bulk tagging.
The verdict
These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-5 nano works out roughly 25x cheaper per blended million tokens. Gemini 2.5 Pro also takes 1.0M of context versus 400K for GPT-5 nano.
Specs & pricing
| Gemini 2.5 Pro | GPT-5 nano | |
|---|---|---|
| modhub Index | 70.9 | — |
| Input price / 1M | $1.25 | $0.05 |
| Output price / 1M | $10 | $0.4 |
| Context window | 1.0M | 400K |
| Max output | 66K | 128K |
| Open weights | no | no |
| Reasoning model | yes | yes |
| Multimodal input | text, image, audio, video | text, image |
| Knowledge cutoff | Jan 2025 | May 2024 |
| Released | Mar 2025 | Aug 2025 |
| Example monthly cost* | $27.50 | $1.10 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, Gemini 2.5 Pro or GPT-5 nano?
- These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-5 nano works out roughly 25x cheaper per blended million tokens. Gemini 2.5 Pro also takes 1.0M of context versus 400K for GPT-5 nano.
- Which is cheaper, Gemini 2.5 Pro or GPT-5 nano?
- Gemini 2.5 Pro costs $1.25/$10 per million input/output tokens, while GPT-5 nano costs $0.05/$0.4. For a typical workload of 10M input and 1.5M output tokens per month, that's $27.50 versus $1.10.
- Which model is better for coding, Gemini 2.5 Pro or GPT-5 nano?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.