Side-by-side comparison
GPT-5 Nano vs Gemini 2.0 Flash
Google
Gemini 2.0 Flash
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.1000
Output / 1M
$0.4000
| GPT-5 Nano | Gemini 2.0 Flash | |
|---|---|---|
| Provider | OpenAI | |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 400,000 | 1,048,576 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0500 | 0.1000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4000 | 0.4000 |
Frequently asked questions
Which is cheaper, GPT-5 Nano or Gemini 2.0 Flash?
GPT-5 Nano is cheaper than Gemini 2.0 Flash on a 50/50 input/output blend by about $0.025 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, GPT-5 Nano or Gemini 2.0 Flash?
Gemini 2.0 Flash has the larger context window at 1M tokens versus 400k tokens for GPT-5 Nano. That means Gemini 2.0 Flash can ingest about 2.6x as much text per request.
What is the difference between GPT-5 Nano and Gemini 2.0 Flash?
GPT-5 Nano comes from OpenAI; Gemini 2.0 Flash comes from Google. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.