Side-by-side technical and economic comparison between OpenAI's GPT-5.6 Terra and Meta / Together's Llama 4 Vivas.
| Metric | GPT-5.6 Terra | Llama 4 Vivas | Advantage |
|---|---|---|---|
| Provider Organization | OpenAI | Meta / Together | — |
| Standard Input / 1M | $2.00 | $0.25 | Llama 4 Vivas (88% lower) |
| Cached Input / 1M | $0.20 | $0.06 | Llama 4 Vivas lower |
| Output / 1M | $12.00 | $0.85 | Llama 4 Vivas lower |
| Context Window | 1.05M | 1M | GPT-5.6 Terra (1.05M) |
| Max Generation Tokens | 16.4k | 128k | Llama 4 Vivas |
| Tokenizer Family | OpenAI o200k_base (200k vocabulary) | Meta Llama 3 Tokenizer (128k vocabulary) | — |
| Workload (per month) | GPT-5.6 Terra | Llama 4 Vivas |
|---|---|---|
| Chatbot10k requests · 500 in / 200 out | $34.00 | $2.95 |
| RAG app100k requests · 8,000 in / 1,200 out | $3,040.00 | $302.00 |
| Coding agent100k requests · 12,000 in / 2,000 out | $4,800.00 | $470.00 |
Standard rates, no caching or batch discounts. Model your own numbers below.
Opt for GPT-5.6 Terra 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 $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.
At a typical 3:1 input-to-output token mix, Llama 4 Vivas is about 91% cheaper than GPT-5.6 Terra. GPT-5.6 Terra costs $2 per 1M input and $12 per 1M output tokens; Llama 4 Vivas costs $0.25 and $0.85.
GPT-5.6 Terra has the larger context window: 1.05M tokens vs 1M.
GPT-5.6 Terra: yes, cached input costs $0.2/1M. Llama 4 Vivas: yes, cached input costs $0.06/1M.