GPT-5.6 Terra
GPT-5.6 model that balances intelligence and cost
GPT-5.6 Terra is a specific OpenAI AI model release referenced for Codex and API use, including lower-cost coding and reasoning workloads.
Pricing
Prompts with more than 272K input tokens are priced at 2x input and 1.5x output for the full request. Cache writes are billed at 1.25x uncached input token rate.
OpenAI's official model documentation identifies GPT-5.6 Terra as accepting text and image input, and states token-based pricing: $2 per 1M input tokens, $0.20 per 1M cached input tokens, and $12 per 1M output tokens. Requests over 272K input tokens have a stated surcharge.
Model Intelligence
Recent stories
LangSmith now lets teams score production traces with Jev and trigger automated responses. Tests found Jev fast and competitive for groundedness, but weaker than reasoning models on math and code.
GPT-5.6 Sol now costs $4 per million input tokens and $10 per million output tokens. Benchmark comparisons place Sol at 72.7% on DeepSWE for $6.47 per task, while OpenAI and AWS report lower successful-task costs for Terra in Kiro.
Practitioners reported better Codex multi-agent runs by raising concurrency and splitting work across Sol, Terra, and Luna. One workflow sends deploy tasks to Luna Max to preserve Sol tokens.
Sol-advisor routes Codex tasks through GPT-5.6 Sol, Luna, and Terra, while users compare Luna Max as a lower-cost reasoning setting. Early reports say small routing tests need larger benchmarks.
OpenAI said GPT-5.6 Luna pricing fell 80%, while Terra fell 20%. Codex users recommended max reasoning for linting, tests, and dependency work, but cautioned against forcing Luna into subagent roles.
OpenAI said GPT-5.6 Luna is 80% cheaper and Terra is 20% cheaper, with lower usage burn in Codex and ChatGPT Work. Sol Fast adds up to 2.5x speed at 2x price, and gateways reflected the new pricing.