Side-by-side technical and economic comparison between DeepSeek's DeepSeek-V4.1-Reasoner and Meta / Together's Llama 4 Vivas.
| Metric | DeepSeek-V4.1-Reasoner | Llama 4 Vivas | Advantage |
|---|---|---|---|
| Provider Organization | DeepSeek | Meta / Together | — |
| Standard Input / 1M | $0.50 | $0.25 | Llama 4 Vivas (50% lower) |
| Cached Input / 1M | $0.01 | $0.06 | DeepSeek-V4.1-Reasoner lower |
| Output / 1M | $2.50 | $0.85 | Llama 4 Vivas lower |
| Context Window | 256k | 1M | Llama 4 Vivas (1M) |
| Max Generation Tokens | 384k | 128k | DeepSeek-V4.1-Reasoner |
| Tokenizer Family | DeepSeek Byte-Level BPE (102k vocabulary) | Meta Llama 3 Tokenizer (128k vocabulary) | — |
Opt for DeepSeek-V4.1-Reasoner when your engineering requirements prioritize DeepSeek's ecosystem, specific tokenizer efficiencies (Calibrated DeepSeek Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.5/M input rate.
Opt for Llama 4 Vivas when looking for Meta / Together's tooling integration, specific context window depth (1M tokens), or when output generation volume favors its $0.85/M rate.