Side-by-side technical and economic comparison between OpenAI's OpenAI o1 and DeepSeek's DeepSeek-V4.1-Reasoner.
• OpenAI o1: Classified as a Legacy Reference model (Generally Available).
| Metric | OpenAI o1 | DeepSeek-V4.1-Reasoner | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | DeepSeek | — |
| Standard Input / 1M | $15.00 | $0.50 | DeepSeek-V4.1-Reasoner (97% lower) |
| Cached Input / 1M | $7.50 | $0.01 | DeepSeek-V4.1-Reasoner lower |
| Output / 1M | $60.00 | $2.50 | DeepSeek-V4.1-Reasoner lower |
| Context Window | 200k | 256k | DeepSeek-V4.1-Reasoner (256k) |
| Max Generation Tokens | 100k | 384k | DeepSeek-V4.1-Reasoner |
| Tokenizer Family | OpenAI o200k_base (200k vocabulary) | DeepSeek Byte-Level BPE (102k vocabulary) | — |
Opt for OpenAI o1 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 $15/M input rate.
Opt for DeepSeek-V4.1-Reasoner when looking for DeepSeek's tooling integration, specific context window depth (256k tokens), or when output generation volume favors its $2.5/M rate.