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OpenAI's balanced GPT-5.6 model, offering a 1.05M-token context window and configurable reasoning effort for mid-complexity coding and document tasks.
Overview. GPT-5.6 Terra is OpenAI's mid-tier ('balanced') model in the GPT-5.6 lineup, generally available since July 2026. It pairs a 1.05-million-token context window with a 128K max output and accepts text, image, and file input while returning text. Developers reach for Terra when they want a general-purpose Inference option that balances intelligence and cost without stepping up to a dedicated reasoning-first variant.
Key strengths. Independent Artificial Analysis benchmarking puts Terra's coding index at 76.7, its strongest measured dimension, alongside a general intelligence index of 56.6. It supports a configurable reasoning-effort control (none through max, default medium), letting a request dial up deliberation only when a task needs it. Context caching is available, which helps repeated-prompt workloads reuse earlier context efficiently.
When to use it. Terra fits medium-complexity, interactive workloads: coding assistance, document analysis over long inputs, and general chat or assistant use where a fast, balanced model is preferable to a heavier reasoning-first tier. Its 1.05M-token context window and native file input make it a reasonable choice for tasks that require ingesting large documents or codebases in a single call. Because its measured agentic index (50.2) trails its coding score, it's a better fit for single-turn or lightly agentic tasks than for long multi-step autonomous workflows.
Limitations. Terra is text-and-image-in, text-out only — it has no audio input or output. It's a closed-weight, proprietary model with a training cutoff of February 16, 2026, so it won't have knowledge of events after that date. As the family's balanced mid-tier, it sits below OpenAI's dedicated reasoning-first variant on complex reasoning tasks.
Sovereignty note. GPT-5.6 Terra is built and hosted by OpenAI, a US-based creator, and access is governed by OpenAI's standard API Terms of Use. No EU data-residency or CLOUD Act exposure details were available in research for this model, so it should not be treated as a Sovereign option without separate verification.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €1.81 / 10.89+7 rates | Online |
15 use cases classified by the curator. The note says why.
Same 1.05M context window supports grounding answers across extensive retrieved document sets without truncation.
1.05M-token context window plus vision input lets it ingest and reason over very large or mixed-media document sets in a single pass.
Native vision capability enables direct text-and-image question answering.
Extended-thinking mode combined with a 1.05M-token window suits multi-source synthesis tasks requiring deep, deliberate reasoning over large inputs.
Vision input supports chart-based extraction tasks, though no chart-specific benchmark is documented for this variant.
Extended-thinking mode aids stepwise analytical reasoning; cost-efficient tier suits routine data analysis workloads.
Vision capability combined with a very large context window supports OCR-style extraction from scanned or image-based documents.
General-purpose, cost-efficient balanced-tier model fits everyday drafting tasks without requiring flagship reasoning.
Long context window handles many source documents, but as a mid-tier variant it lacks the flagship-level reasoning score of gpt-5.6-sol for nuanced synthesis.
Mid-tier general-purpose model with large context window supports extended composition, though not positioned as the family's top reasoning/writing option.
OpenAI's US CLOUD Act exposure and closed-weights status make this a poor fit for regulated policy Q&A workloads requiring sovereignty guarantees.
Sourced numbers, not our own evaluations. Percentiles are against the whole Stav catalogue.
Computed from aa-intelligence-index, gpqa-diamond, aa-engineering-index, aa-coding-index, livecodebench, terminal-bench-v4, ifbench, aa-lcr.
curl https://api.stav.ai/v1/chat/completions \
-H "Authorization: Bearer $STAV_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-5.6-terra",
"reasoning_effort": "high",
"messages": [{"role": "user", "content": "Hello!"}]
}'→ X-Stav-Request-Id · X-Stav-Model · X-Stav-Provider → X-Stav-Sovereignty-Level — the rung the request was served at