GPT-6 Astra Reasoning Levels: Choose Effort for the Actual Task
Which GPT-6 Astra Reasoning Levels Are Documented?
The official GPT-6 Astra model page, reviewed on October 20, 2026, lists five API values for reasoning.effort: low, medium, high, xhigh and max. Use the model-specific page when checking support rather than combining values from unrelated models or clients.
OpenAI's reasoning guide states that Astra does not support none. The setting controls the effort directed toward reasoning; it is not a video-resolution setting or an output-length target.
This article explains those documented API settings and an independent evaluation approach. It does not establish which effort choices a particular app exposes, and it does not claim GPT-6 Astra access or an effort selector inside MOVO.
What Does Reasoning Effort Change?
Reasoning effort affects the resources the model can devote to working through a task. The official guide describes a tradeoff involving reasoning depth, response time and token usage. The useful setting depends on whether the additional work improves the result you need.
Keep the task itself clear. A vague request with missing source facts is not repaired simply by choosing a larger setting. Provide the relevant material, constraints and a definition of a successful answer before comparing levels.
A longer or more confident response is not sufficient evidence of a better result. Judge the output by correctness, completeness and usefulness for the task. Verification remains necessary even when a higher setting is selected.
A Practical Way to Compare the Five Levels
Treat low as a candidate for a focused task with clear source material and straightforward acceptance criteria. Medium is another candidate when the task has several connected constraints. These are starting hypotheses to test, not measured performance claims.
Consider high for a task where the lower setting repeatedly misses important relationships or edge cases. Reserve xhigh and max comparisons for genuinely difficult work where you can inspect whether the added effort provides a meaningful benefit.
Keep the prompt and source material stable while comparing. If the task changes at the same time as the setting, you cannot confidently attribute the difference to effort. Record both useful improvements and new mistakes rather than counting only attractive wording.
Use a Creative-Planning Example You Can Verify
Suppose you are planning an original six-scene film about a small brass observatory moving through changing seasons. The task is to produce a shot plan that preserves its design, assigns each season a story role and avoids contradictory camera instructions.
Define review criteria before testing: all required beats appear, each shot has a visible action, references have clear roles and the ending resolves the original idea. Check the generated plan against those criteria without being influenced only by its length.
If one effort level produces a more detailed plan but invents unsupported tool capabilities, it has not solved the task better. Correct the brief or evaluation standard and rerun an appropriate comparison. Creative usefulness still depends on accuracy about the production workflow.
Keep API Settings and App Controls Distinct
For developers, the official model guide identifies reasoning.effort for Responses and reasoning_effort for Chat Completions. It also gives endpoint-specific compatibility guidance. Check current documentation for the complete request you intend to send.
A client can expose a subset or a differently presented control. Do not assume an app label is an exact API contract without checking that client's documentation. Likewise, a supported API value does not establish that your account includes a particular model or service tier.
This page does not call an API, run a benchmark or change your account settings. The illustration is an original planning metaphor, not a screenshot of a model control or evidence of an executed comparison.
Separate Planning Effort From Video Generation Cost
A reasoning model can help organize a script, constraints or review criteria, while the actual media generation may be another operation with its own settings and usage. Higher language-model effort does not by itself imply higher video resolution, better motion or more scene attempts.
Budget the work by stage. Planning, reference creation, video generation, revisions and final audio or caption work can consume different resources. Use actual workspace estimates rather than translating an API effort label into an assumed video-credit price.
The AI video credits guide explains how to organize that production estimate. Keep external API settings distinct from the usage conditions displayed by the service where you create the media.
Bring an Approved Plan Into a MOVO Project
Use the approved story and shot plan to start an original MOVO video brief. Include the audience, subject, scene purpose and authorized references. The useful handoff is the clear creative material, not an assumption that an external model configuration transfers with it.
Test a representative scene and inspect its complete movement and continuity. A well-reasoned written plan still needs visual evidence that the generated scene works. Keep exact text and final synchronization under suitable finishing controls.
Retain the brief, review criteria and approved assets with the project. If the plan or tool options change, revisit the affected scenes rather than relying on the reasoning setting as proof that the whole production is complete.
Frequently Asked Questions
Which API effort values does GPT-6 Astra document?
The model page reviewed October 20, 2026 lists low, medium, high, xhigh and max for reasoning.effort.
Can I set GPT-6 Astra reasoning effort to none?
The official reasoning guide says none is unsupported for Astra. Check current model-specific API documentation.
Does max guarantee a correct answer?
No. Evaluate the output against explicit requirements and verify important facts regardless of the effort level.
Does a higher effort level improve video resolution?
No direct relationship is established. Media generation settings and costs are separate from language-model reasoning effort.
Are the same options available in every app?
Do not assume that. Client controls and account access must be checked separately from the API model page.
Does this article confirm Astra availability in MOVO?
No. Use an approved creative plan in MOVO and check the actual workspace options rather than inferring access from this article.