Side-by-side technical and economic comparison between Meta / Together's Llama 4 Scout (17B Active / 109B MoE) — Together AI and OpenAI's GPT-5.6 Mini.
• Llama 4 Scout (17B Active / 109B MoE) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Llama 4 Scout (17B Active / 109B MoE) — Together AI | GPT-5.6 Mini | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | OpenAI | — |
| Standard Input / 1M | $0.18 | $0.30 | Llama 4 Scout (17B Active / 109B MoE) — Together AI (40% lower) |
| Cached Input / 1M | None | $0.03 | GPT-5.6 Mini lower |
| Output / 1M | $0.59 | $1.20 | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Context Window | 328k | 400k | GPT-5.6 Mini (400k) |
| Max Generation Tokens | 16.4k | 16.4k | Llama 4 Scout (17B Active / 109B MoE) — Together AI |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | OpenAI o200k_base (200k vocabulary) | — |
Opt for Llama 4 Scout (17B Active / 109B MoE) — 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 $0.18/M input rate.
Opt for GPT-5.6 Mini when looking for OpenAI's tooling integration, specific context window depth (400k tokens), or when output generation volume favors its $1.2/M rate.