Side-by-side technical and economic comparison between Meta / Together's Llama 4 Maverick (400B) — Together AI and Google's Gemini 2.5 Flash.
• Llama 4 Maverick (400B) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Llama 4 Maverick (400B) — Together AI | Gemini 2.5 Flash | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | — | |
| Standard Input / 1M | $0.27 | $0.30 | Llama 4 Maverick (400B) — Together AI (10% lower) |
| Cached Input / 1M | None | $0.03 | Gemini 2.5 Flash lower |
| Output / 1M | $0.85 | $2.50 | Llama 4 Maverick (400B) — Together AI lower |
| Context Window | 1M | 1.05M | Gemini 2.5 Flash (1.05M) |
| Max Generation Tokens | 16.4k | 8.2k | Llama 4 Maverick (400B) — Together AI |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | Google Gemma SentencePiece (~256k 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 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.