Side-by-side technical and economic comparison between OpenAI's GPT-5.6 Luna and Google's Gemini 3.8 Flash.
| Metric | GPT-5.6 Luna | Gemini 3.8 Flash | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | — | |
| Standard Input / 1M | $0.20 | $0.75 | GPT-5.6 Luna (73% lower) |
| Cached Input / 1M | $0.02 | $0.075 | GPT-5.6 Luna lower |
| Output / 1M | $1.20 | $3.75 | GPT-5.6 Luna lower |
| Context Window | 1.05M | 1.05M | GPT-5.6 Luna (1.05M) |
| Max Generation Tokens | 16.4k | 16.4k | GPT-5.6 Luna |
| Tokenizer Family | OpenAI o200k_base (200k vocabulary) | Google Gemini SentencePiece (256k vocabulary) | — |
Opt for GPT-5.6 Luna when your engineering requirements prioritize OpenAI's ecosystem, specific tokenizer efficiencies (Exact BPE (o200k_base)), or when your expected prompt-to-completion ratios favor its $0.2/M input rate.
Opt for Gemini 3.8 Flash when looking for Google's tooling integration, specific context window depth (1.05M tokens), or when output generation volume favors its $3.75/M rate.