Side-by-side technical and economic comparison between Google's Gemini 2.5 Flash-Lite and Mistral AI's Mistral Small 4.
| Metric | Gemini 2.5 Flash-Lite | Mistral Small 4 | Advantage |
|---|---|---|---|
| Provider Organization | Mistral AI | — | |
| Standard Input / 1M | $0.10 | $0.15 | Gemini 2.5 Flash-Lite (33% lower) |
| Cached Input / 1M | $0.03 | $0.03 | Gemini 2.5 Flash-Lite lower |
| Output / 1M | $0.40 | $0.60 | Gemini 2.5 Flash-Lite lower |
| Context Window | 1.05M | 128k | Gemini 2.5 Flash-Lite (1.05M) |
| Max Generation Tokens | 8.2k | 8.2k | Gemini 2.5 Flash-Lite |
| Tokenizer Family | Google Gemini SentencePiece (256k vocabulary) | Mistral Tekken Tokenizer (131k 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 Mistral Small 4 when looking for Mistral AI's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $0.6/M rate.