Side-by-side technical and economic comparison between Alibaba / Qwen's Qwen 2.5 72B Instruct — Together AI and Google's Gemini 2.5 Flash.
• Qwen 2.5 72B Instruct — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Qwen 2.5 72B Instruct — Together AI | Gemini 2.5 Flash | Advantage |
|---|---|---|---|
| Provider Organization | Alibaba / Qwen | — | |
| Standard Input / 1M | $0.35 | $0.30 | Gemini 2.5 Flash (14% lower) |
| Cached Input / 1M | $0.175 | $0.03 | Gemini 2.5 Flash lower |
| Output / 1M | $0.40 | $2.50 | Qwen 2.5 72B Instruct — Together AI lower |
| Context Window | 128k | 1.05M | Gemini 2.5 Flash (1.05M) |
| Max Generation Tokens | 8.2k | 8.2k | Qwen 2.5 72B Instruct — Together AI |
| Tokenizer Family | Qwen Byte-level BPE (~152k vocabulary) | Google Gemma SentencePiece (~256k 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 Gemini 2.5 Flash when looking for Google's tooling integration, specific context window depth (1.05M tokens), or when output generation volume favors its $2.5/M rate.