Side-by-side technical and economic comparison between Google's Gemini 2.5 Flash and OpenAI's GPT-5.6 Mini.
| Metric | Gemini 2.5 Flash | GPT-5.6 Mini | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | — | |
| Standard Input / 1M | $0.30 | $0.30 | Identical |
| Cached Input / 1M | $0.03 | $0.03 | GPT-5.6 Mini lower |
| Output / 1M | $2.50 | $1.20 | GPT-5.6 Mini lower |
| Context Window | 1.05M | 400k | Gemini 2.5 Flash (1.05M) |
| Max Generation Tokens | 8.2k | 16.4k | GPT-5.6 Mini |
| Tokenizer Family | Google Gemma SentencePiece (~256k vocabulary) | OpenAI o200k_base (200k vocabulary) | — |
Opt for Gemini 2.5 Flash when your engineering requirements prioritize Google's ecosystem, specific tokenizer efficiencies (Calibrated Gemma Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.3/M input rate.
Opt for GPT-5.6 Mini when looking for OpenAI's tooling integration, specific context window depth (400k tokens), or when output generation volume favors its $1.2/M rate.