Side-by-side technical and economic comparison between Meta / Together's Llama 4 Maverick (400B) — Together AI and Alibaba / Qwen's Qwen3 235B-A22B.
• Llama 4 Maverick (400B) — Together AI: Classified as a Legacy Reference model (Deprecated on Together AI (Reference)).
| Metric | Llama 4 Maverick (400B) — Together AI | Qwen3 235B-A22B | Advantage |
|---|---|---|---|
| Provider Organization | Meta / Together | Alibaba / Qwen | — |
| Standard Input / 1M | $0.27 | $0.90 | Llama 4 Maverick (400B) — Together AI (70% lower) |
| Cached Input / 1M | None | $0.18 | Llama 4 Maverick (400B) — Together AI lower |
| Output / 1M | $0.85 | $1.60 | Llama 4 Maverick (400B) — Together AI lower |
| Context Window | 1M | 128k | Llama 4 Maverick (400B) — Together AI (1M) |
| Max Generation Tokens | 16.4k | 32k | Qwen3 235B-A22B |
| Tokenizer Family | Meta Llama 3/4 Tiktoken (128k vocabulary) | Qwen SentencePiece BPE (152k 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 Qwen3 235B-A22B when looking for Alibaba / Qwen's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $1.6/M rate.