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OpenAI's flagship closed-weight reasoning model with a 1.05M-token context window and mandatory reasoning on every request.
Overview. GPT-6 Astra is OpenAI's flagship closed-weight reasoning model, released in September 2026 as the successor to the GPT-5.6 line. It pairs a 1,050,000-token context window with mandatory reasoning on every request, accepting text, image, and file inputs and returning text. Developers reach for it when a task demands sustained, deliberate reasoning over very large documents or codebases rather than a fast, low-effort response.
Key strengths. GPT-6 Astra's reasoning cannot be switched off — every request runs through OpenAI's reasoning process, with effort configurable from low through max. Its 1,050,000-token context window is the largest in the catalogue, and its input modalities extend beyond text and images to file uploads, supporting native document understanding. Independent trackers place it as OpenAI's new frontier-tier flagship, and it is reported as the first OpenAI model assessed at the 'Critical' level under OpenAI's own Preparedness Framework for cybersecurity capability — a marker of how far its raw reasoning capability extends, alongside the misuse-risk considerations that come with it.
When to use it. Use GPT-6 Astra for reasoning-heavy work — complex analysis, multi-step problem solving, or agentic tool-use flows via the Responses API — where quality matters more than raw speed. Its 1.05M-token window and file-input support make it well suited to reasoning over long documents, large codebases, or multi-document research tasks in a single call. Setting reasoning effort to low keeps it usable at interactive, seconds-scale latency; higher effort settings trade latency for deeper reasoning on harder problems.
Limitations. GPT-6 Astra does not support custom temperature, top_p, or logprobs — output shaping happens only through reasoning-effort settings, not classic sampling controls. Tool calling requires OpenAI's Responses API rather than Chat Completions, so integrations built against the older API surface will need updating. As a closed-weight model, OpenAI has not disclosed its parameter count or architecture, and its knowledge cutoff is April 30, 2026.
Sovereignty note. GPT-6 Astra is created by OpenAI, a US-based company, so requests may be subject to CLOUD Act exposure rather than EU-only jurisdiction. Research did not confirm specific data-residency or training-on-input policy details for this endpoint, so no further claim is made here.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €9.07 / 45.37+9 rates | Online |
40 use cases classified by the curator. The note says why.
Tool-calling enables action in coding environments, and extended thinking plus a 1.05M-token context window supports complex, repository-scale tasks.
The 1.05M-token context window supports answering over very large document sets, and extended thinking can synthesize information across them.
Extended thinking supports tracing complex failure causes, and the large context window can retain extensive code, logs, and diagnostic evidence.
The 1.05M-token context window supports explanations grounded in large repositories, and extended thinking can connect behavior across files.
The 1.05M-token context window can accommodate large codebases or extensive diffs, while extended thinking supports reasoning across changes.
The 1.05M-token context window enables question answering over exceptionally long documents, with extended thinking supporting cross-document reasoning.
A 1.05M-token context and extended reasoning are useful for reviewing and cross-referencing large audit records, though no audit-specific validation is reported.
Tool-calling enables browser-action workflows, while extended reasoning supports multi-step execution; no browser-specific benchmark or capability is provided.
Vision capability provides a direct basis for interpreting chart images, with extended thinking supporting explanations; no chart-specific benchmark is listed.
Vision capability supports reading chart content, but no chart-extraction benchmark or structured output guarantee is provided.
Extended reasoning and the large context window support classification tasks with complex criteria or extensive input; no classification score is available.
The large context window can include substantial surrounding code, and tool-calling supports coding workflows; no code benchmark is provided.
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, 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-6-astra",
"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