Side-by-side technical and economic comparison between Meta / Together's Llama 4 Maverick (400B) — Together AI and DeepSeek's DeepSeek-V4.1-Reasoner.
• Llama 4 Maverick (400B) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Llama 4 Maverick (400B) — Together AI | DeepSeek-V4.1-Reasoner | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | DeepSeek | — |
| Standard Input / 1M | $0.27 | $0.50 | Llama 4 Maverick (400B) — Together AI (46% lower) |
| Cached Input / 1M | None | $0.01 | DeepSeek-V4.1-Reasoner lower |
| Output / 1M | $0.85 | $2.50 | Llama 4 Maverick (400B) — Together AI lower |
| Context Window | 1M | 256k | Llama 4 Maverick (400B) — Together AI (1M) |
| Max Generation Tokens | 16.4k | 384k | DeepSeek-V4.1-Reasoner |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | DeepSeek Byte-Level BPE (102k vocabulary) | — |
Opt for Llama 4 Maverick (400B) — Together AI when your engineering requirements prioritize Meta / Together's ecosystem, specific tokenizer efficiencies (Calibrated Llama 3 Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.27/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.