Side-by-side technical and economic comparison between Meta / Together's Llama 4 Scout (17B Active / 109B MoE) — Together AI and xAI's Grok 4.6 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 | Grok 4.6 Mini | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | xAI | — |
| Standard Input / 1M | $0.18 | $0.40 | Llama 4 Scout (17B Active / 109B MoE) — Together AI (55% lower) |
| Cached Input / 1M | None | $0.10 | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Output / 1M | $0.59 | $1.60 | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Context Window | 328k | 512k | Grok 4.6 Mini (512k) |
| Max Generation Tokens | 16.4k | 64k | Grok 4.6 Mini |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | OpenAI o200k_base legacy (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 Grok 4.6 Mini when looking for xAI's tooling integration, specific context window depth (512k tokens), or when output generation volume favors its $1.6/M rate.