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OpenAI's flagship GPT-5.6 reasoning model for agentic coding, cybersecurity, and long-horizon analysis, with a 1.05M-token context window.
Overview. GPT-5.6 Sol is OpenAI's flagship reasoning model in the GPT-5 family, sitting alongside the Terra and Luna tiers as the variant tuned for extended thinking. It offers a 1.05M-token context window with up to 128K tokens of output, accepts text, image, and file input, and returns text. Developers reach for Sol when a task needs sustained multi-step reasoning over a very large amount of context rather than a fast, low-latency reply.
Key strengths. Within the GPT-5 family, Sol carries the highest quality index (60.9 on Artificial Analysis' intelligence index), with a coding index of 77.4 and an agentic index of 57.8, reflecting particular strength in coding and multi-step agentic tool-use tasks. It exposes selectable reasoning effort (from none up to max), letting a caller trade latency for deeper deliberation and a visible reasoning trace on demand. Native tool calling and structured output support make it well suited to agentic workflows that chain multiple actions together.
When to use it. Use Sol for long-horizon analysis, multi-step agentic coding, or cybersecurity-style tasks where the model needs to reason across large amounts of context and call tools along the way. Its 1.05M-token window is well suited to whole-codebase or multi-document review where smaller-context models would need chunking. Because it's a reasoning-tagged model with configurable effort levels, it fits best where output quality on hard problems matters more than raw response speed.
Limitations. Sol runs with higher latency than instruct-tier siblings, especially at higher reasoning-effort settings, so it isn't the right fit for latency-sensitive, chat-speed interactions. It accepts text, image, and file input but has no audio input or output, and it's closed-weight and API-only, so there's no option to self-host or fine-tune the underlying weights. Its knowledge cutoff is February 2026.
Sovereignty note. GPT-5.6 Sol is built and hosted by OpenAI, a US-based creator, and is subject to CLOUD Act exposure rather than EU data-residency guarantees. Treat it as a non-Sovereign option and route data-residency-sensitive workloads elsewhere.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €3.59 / 17.93+7 rates | Online |
15 use cases classified by the curator. The note says why.
Explicitly positioned as OpenAI's flagship reasoning model for agentic coding with extended-thinking and a 1.05M-token context window, enabling long-horizon multi-file code tasks.
Flagship reasoning tier with extended-thinking is well suited to tracing complex, long-horizon bugs across large codebases given the 1.05M context window.
As a flagship agentic-coding model, it is well positioned to explain complex code with deep reasoning, aided by its extended-thinking mode.
1.05M-token context supports whole-repository review, and extended-thinking mode aids deep reasoning about code correctness and design tradeoffs.
Long-context (1.05M tokens) plus extended-thinking makes this well suited to deep Q&A over lengthy or numerous documents.
Massive context window (1.05M tokens) allows ingesting many documents at once, ideal for literature-review workloads requiring cross-document reasoning.
Flagship reasoning tier with extended-thinking should handle analytical tasks well, though no data-analysis-specific benchmark is available.
As the flagship agentic-coding model in the family, it should handle function-calling workflows competently, though no explicit function-calling benchmark is cited.
Extended-thinking and huge context support sustained long-form output, though the model's described strengths center on coding and analysis rather than writing quality.
Large context window supports summarizing long documents, though summarisation isn't a headline capability for this variant versus its coding/reasoning focus.
Strong reasoning and large context support generating comprehensive test suites, though this isn't a specifically highlighted strength.
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-sol",
"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