{"id":"astra","level":"model","name":"GPT-6 Astra","shortName":"Astra","role":"Connect documented model capabilities to a larger system of context, tools, and evaluation.","description":"GPT-6 Astra is the named model at this atlas’s contemporary endpoint. OpenAI documents support for reasoning, coding, research, computer use, and document creation, with text input/output and image input. Its published API limits describe the service interface. They do not disclose a parameter count, layer count, attention layout, training cluster, or physical deployment. The surrounding application supplies context, tools, and execution controls. The earlier anatomical views teach published mechanisms and reference hardware, while this view shows the boundary between those concepts and what is actually documented for Astra.\n\nA model service can be studied through its observable interface without inventing its private internals. A recorded request, tool proposal, output event, configuration identity and timing observation establish different facts from an undisclosed architecture diagram. When a real model adapter is added to an execution experience, its observable proposals should be preserved and passed through the same runtime checks as any other policy.","mechanism":["An application assembles instructions, input, prior context, and permitted tools.","Astra generates a response or tool calls; a runtime handles allowed actions and returns results.","The application presents the result and evaluates it against the task’s actual success criteria.","A trace names the actual service/model configuration and records observable input/output fields at a declared boundary.","Runtime authority, approval and external task checks remain independent of the service’s product identity or confidence."],"specs":[{"label":"API context window","value":"1,050,000 tokens","context":"Official GPT-6 Astra model reference, verified September 6, 2026; client applications can impose their own limits."},{"label":"Maximum API output","value":"128,000 tokens","context":"Generated-token budget includes reasoning and other counted generated tokens, not only visible prose."},{"label":"Modalities","value":"Text input/output · image input","context":"Native audio and video are listed as unsupported; separate tools can supply additional media capabilities."},{"label":"Structured interaction","value":"Function calling · structured outputs","context":"Tool calling requires the Responses API, according to the September 3, 2026 changelog."}],"interfaces":[{"name":"Application context","direction":"in","signal":"Instructions, text, images, and supplied tool results"},{"name":"Application runtime","direction":"out","signal":"Generated responses and supported structured tool calls"}],"tradeoff":"A larger accepted context creates room for more material, but reliable use of that material remains task-dependent. Tools extend what an application can accomplish while adding execution, state-management, and verification requirements.","whyAI":"Astra provides a concrete present-day interface for exploring how a learned model and a surrounding runtime work together. Its public limits give learners measurable specifications without presenting an imagined internal blueprint.","related":["tool-loop","evaluation","kv-cache","post-training","scaling-laws","tool-contracts-schemas","tool-authority-identity","telemetry-traces-evaluation"],"sources":[{"title":"OpenAI — GPT-6 Astra Model","url":"https://developers.openai.com/api/docs/models/gpt-6-astra"},{"title":"OpenAI API Changelog — September 3, 2026","url":"https://developers.openai.com/api/docs/changelog"},{"title":"OpenAI — Reasoning Models: Context and Output Accounting","url":"https://developers.openai.com/api/docs/guides/reasoning"},{"title":"MCP tools","url":"https://modelcontextprotocol.io/specification/2026-07-28/server/tools"}],"scale":"Public model-service interface · physical internals undisclosed","kind":"astra","misconception":"A published context length is a token-budget specification; it does not reveal the number of layers, model parameters, GPUs, or an AGI threshold.","check":{"question":"What does Astra’s published context limit establish?","options":["A bound on the documented API token context","Its exact parameter count and GPU allocation","Perfect recall and general intelligence"],"answer":0,"explanation":"The reference specifies an interface limit. Architecture and task reliability require separate evidence."},"branch":"Agent systems","subbranch":"Documented contemporary model","science":[{"title":"Visible output shares a generated-token budget","equation":"G = R + V + F; I + G ≤ C; G ≤ O_max","explanation":"I is the counted input context, R generated reasoning tokens, V visible output tokens, and F other counted generated formatting tokens. C is the context limit and O_max the effective output cap. Reserving output room therefore requires accounting for more than the prose the user sees.","assumptions":"A simplified budget for one model sampling segment with fixed input; use actual API token accounting and configured limits. Tool loops, retained reasoning, multimodal tokenization, and compaction affect later segments. These symbols do not describe hidden model dimensions."}],"history":[{"year":2026,"title":"GPT-6 Astra released through the OpenAI API","significance":"The September 3 API changelog announced Astra for complex tasks using supplied context and tools, with tool calling through the Responses API. This is a product milestone, not a declaration of AGI.","source":{"title":"OpenAI API Changelog — September 3, 2026","url":"https://developers.openai.com/api/docs/changelog"}}],"prerequisites":["tool-loop","evaluation"],"learningObjective":"Apply a declared service token budget without inferring undisclosed model architecture or hardware.","engineeringExample":"Synthetic service example, unrelated to Astra’s published limits: context allowance C = 32,000 tokens, output cap Omax = 8,000 and counted input I = 28,000 leave at most 4,000 generated tokens. If reasoning uses 1,500 and other counted output uses 100, at most 2,400 remain for visible output in this simplified segment.\n\nA captured service response might propose reserve_part for FAN-7 with quantity two. That establishes an observable proposed call, not that the service has permission to execute it, that a reservation occurred, or how many hidden layers produced it. The current incident experience uses an authored policy and a future adapter contract; it does not invoke Astra or another real model.","evidenceNotes":"The example applies the token-accounting relation already stated in the lesson. These are invented limits, not a current OpenAI specification. Actual service accounting, tools and multimodal inputs require the cited interface documentation; no parameter count, training cluster or private design is inferred.\n\nNo new private architecture, current product capability or actual-model execution claim is introduced. The existing public-service source boundary remains intact.","checks":[{"question":"What does a recorded model tool proposal establish?","options":["An observable requested operation","That the operation already committed","The model’s undisclosed parameter count"],"answer":0,"explanation":"The proposal is one observable output; permissions, execution and private internals are separate questions."}],"labId":"library","scope":"Use the execution investigation for the shared tensor-to-memory-to-result thread; no current standalone calculator models this lesson’s full mechanism.","investigationId":"execution","labScope":"Use the execution investigation for the shared tensor-to-memory-to-result thread; no current standalone calculator models this lesson’s full mechanism."}