Side-by-side technical and economic comparison between Google's Gemini 2.5 Flash-Lite and OpenAI's OpenAI o1.
• OpenAI o1: Classified as a Legacy Reference model (Generally Available).
| Metric | Gemini 2.5 Flash-Lite | OpenAI o1 | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | — | |
| Standard Input / 1M | $0.10 | $15.00 | Gemini 2.5 Flash-Lite (99% lower) |
| Cached Input / 1M | $0.01 | $7.50 | Gemini 2.5 Flash-Lite lower |
| Output / 1M | $0.40 | $60.00 | Gemini 2.5 Flash-Lite lower |
| Context Window | 1.05M | 200k | Gemini 2.5 Flash-Lite (1.05M) |
| Max Generation Tokens | 8.2k | 100k | OpenAI o1 |
| Tokenizer Family | Google Gemini SentencePiece (256k vocabulary) | OpenAI o200k_base (200k vocabulary) | — |
Opt for Gemini 2.5 Flash-Lite when your engineering requirements prioritize Google's ecosystem, specific tokenizer efficiencies (Calibrated Gemini Tokenizer (±4%)), or when your expected prompt-to-completion ratios favor its $0.1/M input rate.
Opt for OpenAI o1 when looking for OpenAI's tooling integration, specific context window depth (200k tokens), or when output generation volume favors its $60/M rate.