Side-by-side technical and economic comparison between Anthropic's Claude Haiku 4.5 and Mistral AI's Codestral (Current Generation).
| Metric | Claude Haiku 4.5 | Codestral (Current Generation) | Advantage |
|---|---|---|---|
| Provider Organization | Anthropic | Mistral AI | — |
| Standard Input / 1M | $1.00 | $0.30 | Codestral (Current Generation) (70% lower) |
| Cached Input / 1M | $0.10 | $0.03 | Codestral (Current Generation) lower |
| Output / 1M | $5.00 | $0.90 | Codestral (Current Generation) lower |
| Context Window | 200k | 256k | Codestral (Current Generation) (256k) |
| Max Generation Tokens | 8.2k | 8.2k | Claude Haiku 4.5 |
| Tokenizer Family | Anthropic Claude BPE (~65k vocabulary) | Mistral Tekken BPE (~131k vocabulary) | — |
Opt for Claude Haiku 4.5 when your engineering requirements prioritize Anthropic's ecosystem, specific tokenizer efficiencies (Calibrated Claude Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $1/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.