Side-by-side technical and economic comparison between Google's Gemini 2.5 Flash and Meta / Together's Llama 3.1 405B — Together AI.
• Llama 3.1 405B — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Gemini 2.5 Flash | Llama 3.1 405B — Together AI | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | — | |
| Standard Input / 1M | $0.30 | $3.50 | Gemini 2.5 Flash (91% lower) |
| Cached Input / 1M | $0.03 | None | Gemini 2.5 Flash lower |
| Output / 1M | $2.50 | $3.50 | Gemini 2.5 Flash lower |
| Context Window | 1.05M | 128k | Gemini 2.5 Flash (1.05M) |
| Max Generation Tokens | 8.2k | 4.1k | Gemini 2.5 Flash |
| Tokenizer Family | Google Gemma SentencePiece (~256k vocabulary) | Meta Llama 3 Tiktoken BPE (~128k vocabulary) | — |
Opt for Gemini 2.5 Flash when your engineering requirements prioritize Google's ecosystem, specific tokenizer efficiencies (Calibrated Gemma Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.3/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.