Side-by-side technical and economic comparison between Meta / Together's Llama 4 Scout (17B Active / 109B MoE) — Together AI and Alibaba / Qwen's Qwen 2.5 Coder 32B — Together AI.
• Qwen 2.5 Coder 32B — Together AI: Listed on Together AI catalog at $0.80/M in, $0.80/M out. The serverless endpoint is launching soon and not yet live in production.
• Llama 4 Scout (17B Active / 109B MoE) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
• Qwen 2.5 Coder 32B — Together AI: Classified as a Legacy Reference model (Listed ($0.80/M) — Endpoint Launching Soon (Not Live)).
| Metric | Llama 4 Scout (17B Active / 109B MoE) — Together AI | Qwen 2.5 Coder 32B — Together AI | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | Alibaba / Qwen | — |
| Standard Input / 1M | $0.18 | $0.80 | Llama 4 Scout (17B Active / 109B MoE) — Together AI (78% lower) |
| Cached Input / 1M | None | None | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Output / 1M | $0.59 | $0.80 | Llama 4 Scout (17B Active / 109B MoE) — Together AI lower |
| Context Window | 328k | 128k | Llama 4 Scout (17B Active / 109B MoE) — Together AI (328k) |
| Max Generation Tokens | 16.4k | 8.2k | Llama 4 Scout (17B Active / 109B MoE) — Together AI |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | Qwen Byte-level BPE (~152k 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 Qwen 2.5 Coder 32B — Together AI when looking for Alibaba / Qwen's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $0.8/M rate.