Side-by-side technical and economic comparison between Mistral AI's Mistral Small 4 and OpenAI's GPT-5.6 Luna.
| Metric | Mistral Small 4 | GPT-5.6 Luna | Advantage |
|---|---|---|---|
| Provider Organization | Mistral AI | OpenAI | — |
| Standard Input / 1M | $0.15 | $0.20 | Mistral Small 4 (25% lower) |
| Cached Input / 1M | $0.015 | $0.02 | Mistral Small 4 lower |
| Output / 1M | $0.60 | $1.20 | Mistral Small 4 lower |
| Context Window | 256k | 1.05M | GPT-5.6 Luna (1.05M) |
| Max Generation Tokens | 8.2k | 16.4k | GPT-5.6 Luna |
| Tokenizer Family | Mistral Tekken Tokenizer (131k vocabulary) | OpenAI o200k_base (200k vocabulary) | — |
Opt for Mistral Small 4 when your engineering requirements prioritize Mistral AI's ecosystem, specific tokenizer efficiencies (Calibrated Mistral Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.15/M input rate.
Opt for GPT-5.6 Luna when looking for OpenAI's tooling integration, specific context window depth (1.05M tokens), or when output generation volume favors its $1.2/M rate.