Side-by-side technical and economic comparison between OpenAI's GPT-5.6 Luna and Meta / Together's Llama 4 Vivas.
| Metric | GPT-5.6 Luna | Llama 4 Vivas | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | Meta / Together | — |
| Standard Input / 1M | $0.20 | $0.25 | GPT-5.6 Luna (20% lower) |
| Cached Input / 1M | $0.02 | $0.06 | GPT-5.6 Luna lower |
| Output / 1M | $1.20 | $0.85 | Llama 4 Vivas lower |
| Context Window | 1.05M | 1M | GPT-5.6 Luna (1.05M) |
| Max Generation Tokens | 16.4k | 128k | Llama 4 Vivas |
| Tokenizer Family | OpenAI o200k_base (200k vocabulary) | Meta Llama 3 Tokenizer (128k vocabulary) | — |
Opt for GPT-5.6 Luna 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 $0.2/M input rate.
Opt for Llama 4 Vivas when looking for Meta / Together's tooling integration, specific context window depth (1M tokens), or when output generation volume favors its $0.85/M rate.