Side-by-side technical and economic comparison between Google's Gemini 3.8 Flash and OpenAI's GPT-5.6 Terra.
| Metric | Gemini 3.8 Flash | GPT-5.6 Terra | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | — | |
| Standard Input / 1M | $0.75 | $2.00 | Gemini 3.8 Flash (63% lower) |
| Cached Input / 1M | $0.07 | $1.00 | Gemini 3.8 Flash lower |
| Output / 1M | $3.75 | $12.00 | Gemini 3.8 Flash lower |
| Context Window | 1.05M | 128k | Gemini 3.8 Flash (1.05M) |
| Max Generation Tokens | 16.4k | 16.4k | Gemini 3.8 Flash |
| Tokenizer Family | Google Gemini SentencePiece (256k vocabulary) | OpenAI o200k_base (200k vocabulary) | — |
Opt for Gemini 3.8 Flash 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 $0.75/M input rate.
Opt for GPT-5.6 Terra when looking for OpenAI's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $12/M rate.