Side-by-side technical and economic comparison between Google's Gemini 3.8 Flash and Mistral AI's Codestral (Current Generation).
| Metric | Gemini 3.8 Flash | Codestral (Current Generation) | Advantage |
|---|---|---|---|
| Provider Organization | Mistral AI | — | |
| Standard Input / 1M | $0.75 | $0.30 | Codestral (Current Generation) (60% lower) |
| Cached Input / 1M | $0.075 | $0.03 | Codestral (Current Generation) lower |
| Output / 1M | $3.75 | $0.90 | Codestral (Current Generation) lower |
| Context Window | 1.05M | 256k | Gemini 3.8 Flash (1.05M) |
| Max Generation Tokens | 16.4k | 8.2k | Gemini 3.8 Flash |
| Tokenizer Family | Google Gemini SentencePiece (256k vocabulary) | Mistral Tekken BPE (~131k 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 Codestral (Current Generation) when looking for Mistral AI's tooling integration, specific context window depth (256k tokens), or when output generation volume favors its $0.9/M rate.