Side-by-side technical and economic comparison between OpenAI's OpenAI o3-pro and Meta / Together's Llama 4 Scout (17B Active / 109B MoE) — Together AI.
• Llama 4 Scout (17B Active / 109B MoE) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | OpenAI o3-pro | Llama 4 Scout (17B Active / 109B MoE) — Together AI | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | Meta / Together | — |
| Standard Input / 1M | $20.00 | $0.18 | Llama 4 Scout (17B Active / 109B MoE) — Together AI (99% lower) |
| Cached Input / 1M | None | None | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Output / 1M | $80.00 | $0.59 | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Context Window | 256k | 328k | Llama 4 Scout (17B Active / 109B MoE) — Together AI (328k) |
| Max Generation Tokens | 100k | 16.4k | OpenAI o3-pro |
| Tokenizer Family | OpenAI o200k_base (200k vocabulary) | Meta Llama 3/4 Tiktoken (128k vocabulary) | — |
Opt for OpenAI o3-pro when your engineering requirements prioritize OpenAI's ecosystem, specific tokenizer efficiencies (Exact BPE (o200k_base)), or when your expected prompt-to-completion ratios favor its $20/M input rate.
Opt for Llama 4 Scout (17B Active / 109B MoE) — Together AI when looking for Meta / Together's tooling integration, specific context window depth (328k tokens), or when output generation volume favors its $0.59/M rate.