Side-by-side technical and economic comparison between Alibaba / Qwen's Qwen 2.5 72B Instruct — Together AI and Meta / Together's Llama 3.1 405B — Together AI.
• Qwen 2.5 72B Instruct — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
• Llama 3.1 405B — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Qwen 2.5 72B Instruct — Together AI | Llama 3.1 405B — Together AI | Advantage |
|---|---|---|---|
| Provider Organization | Alibaba / Qwen | Meta / Together | — |
| Standard Input / 1M | $0.35 | $3.50 | Qwen 2.5 72B Instruct — Together AI (90% lower) |
| Cached Input / 1M | $0.175 | None | Qwen 2.5 72B Instruct — Together AI lower |
| Output / 1M | $0.40 | $3.50 | Qwen 2.5 72B Instruct — Together AI lower |
| Context Window | 128k | 128k | Equal |
| Max Generation Tokens | 8.2k | 4.1k | Qwen 2.5 72B Instruct — Together AI |
| Tokenizer Family | Qwen Byte-level BPE (~152k vocabulary) | Meta Llama 3 Tiktoken BPE (~128k vocabulary) | — |
Opt for Qwen 2.5 72B Instruct — Together AI when your engineering requirements prioritize Alibaba / Qwen's ecosystem, specific tokenizer efficiencies (Calibrated Qwen Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.35/M input rate.
Opt for Llama 3.1 405B — Together AI when looking for Meta / Together's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $3.5/M rate.