YouMind
Sign in

GPT-6 Astra

Bring a difficult question, the material behind it and the constraints that matter. GPT-6 Astra helps connect the evidence, weigh alternatives and turn the result into a clear brief you can keep refining.

GPT-6 Astra
Research
Webpage
Slides
Image
Video

What GPT-6 Astra does best

  • Work through complex questions

    Explore problems with several dependencies and ask for the assumptions, alternatives and checks that support a recommendation.

  • Read text and visual references

    Combine written context with images when a diagram, screenshot or photograph contains details relevant to your question.

  • Refine the depth of a response

    Choose a reasoning effort suited to the task, then continue with focused followup questions as the brief develops.

Make complex material useful with GPT-6 Astra

Research synthesis with source connections

Turn notes, reports and observations into a coherent research brief with GPT-6 Astra. Astra connects relevant evidence around your question, keeps conflicting claims visible and helps you trace how each source contributes to the conclusion.

Connect sources into a coherent brief

Decision support with clear tradeoffs

Use GPT-6 Astra to compare options against the budget, timing and dependencies of a project. Work through the tradeoffs and the assumptions behind each direction, then identify what would make a different choice more useful.

Weigh options against real constraints

Image analysis grounded in visible detail

Add an image or screenshot and ask GPT-6 Astra about the part you want to understand. Astra can describe a visible detail, compare it with a reference or develop a focused explanation that helps with a design review or written brief.

Explain what a visual reference shows

Start with a question that matters

  1. Provide the question and evidence

    Paste the relevant notes or add a visual reference. Explain who the result is for, the decision it should support and any constraints the answer must respect.

  2. Continue with the selected model

    Choose Try in YouMind and sign in when prompted. Continue in the conversation with Astra selected, then ask for a brief, comparison or explanation with a clear structure.

  3. Check the recommendation and refine it

    Verify important claims against the sources. Ask about missing assumptions, challenge a weak step, or revise one section while preserving the parts you want to keep.

Compare GPT-6 Astra with other models

Compare model inputs, context, output, reasoning and task focus to choose a starting point.

Compare GPT-6 Astra with other models
CompareGPT-6 AstraClaude Opus 4.6
Model input
Accepts text and images for work involving documents, code and visual references.
Accepts text and images for work involving documents, code and visual references.
Context window
Provides a 1,050,000-token context window.
Provides a 1M-token context window.
Output and length
Produces text with a maximum output of 128,000 tokens for explanations, documents and code.
Produces text with a maximum output of 128K tokens for explanations, documents and code.
Reasoning
Supports Low, Medium, High, Extra high and Max reasoning effort.
Supports adaptive thinking for code review, long documents and complex reasoning.
Task focus
Focuses on demanding reasoning, coding, research and document creation.
Focuses on sustained coding, code review and detailed knowledge work.

Scroll horizontally to compare all models

Prompts to make your own

Explore GPT-6 Astra prompts and find a starting point for your next webpage.

Interactive V8 Engine 3D Model

create a highly detailed, interactive visualization of a V8 engine

GPT-6 Astra Design Workflow with Images 2.5

Use imagegen to reimagine this page, then implement it.

Cozy Creek Three.js Experience with GPT-6 Astra

Create a cozy creek 3D experience running in the browser using Three.js. The assets should be modeled in Blender. Ensure it is interactive and visually appealing as a web-based 3D scene.

Zork Text Adventure to 3D Game

Turn Zork (the classic 1977 text adventure) into a full 3D action-adventure game. Keep the original plot & puzzles, add fight scenes, and build all of the characters & environments directly in Threejs.

Three.js Valorant Ascent Map Generation

make me VALORANT in three.js, make no mistakes. as a map use valorants "ascent" map

High-Density 3D Browser Forest Generator

First search for the "/unlazy" skill, read it fully, and use it throughout the entire task.

Treat this as a major visual build lasting at least {argument name="minimum duration" default="5 hours"}. Prefer {argument name="optimal duration" default="8–24 hours"} of meaningful implementation and iteration if the environment allows it. Do not stop after producing one decent-looking scene.

Create an extremely detailed real-time {argument name="subject" default="3D forest"} in the browser. Nothing else. No landing page, cards, story, marketing UI, dashboard, or unnecessary text. The forest itself is the entire experience.

Push density and visual quality extremely hard.

Build massive amounts of detailed grass, varied trees, branches, leaves, bushes, ferns, moss, flowers, weeds, roots, fallen wood, stones, soil, leaf litter, small plants, terrain variation, and tiny environmental details.

The forest should feel almost excessively dense. Empty ground should be rare.

Focus obsessively on:
realistic tree silhouettes,
dense grass,
natural asset variation,
rich colors,
lighting,
contact shadows,
wind,
foliage motion,
atmospheric depth,
fog,
sun shafts,
particles,
terrain,
materials,
scale,
composition,
and detail at both close and far distances.

Avoid obvious repeating assets, billboard-looking foliage, tiled terrain, floating plants, plastic materials, identical trees, sparse procedural placement, excessive bloom, or a generic Three.js demo appearance.

Include smooth free-camera exploration.

Repeatedly capture and inspect the scene from many positions. Identify weak vegetation, empty areas, bad colors, repetition, poor materials, unrealistic lighting, ugly tree shapes, performance bottlenecks, and anything that breaks immersion. Fix these issues and continue increasing quality throughout the run.

The goal is not feature count. The goal is to make one browser forest look completely ridiculous in terms of detail and atmosphere.

Build the full experience, publish it PUBLICLY on ChatGPT Sites, verify the deployment, and return the public URL.

Astra Blender Rigging Workflow

Pass the .blend file to Astra and ask it to photograph the neutral face from front and side views (with/without vertex/edge display). Use these images with GPT-Image2.5 to generate smiling front/side references. Then instruct Astra to adjust mouth corners, cheeks, eyelids etc. to create shape keys based on the reference images, ensuring original topology is preserved and checking tooth/tongue positions.

Fantasy Island 3D Adventure World

A sunlit fantasy island city. Turquoise waters. Ancient temples. Stone streets. Magical landmarks. And a world that actually feels explorable.

GTA-Inspired 3D Car Chase Pipeline

Create an original {argument name="style" default="GTA-inspired cartoon car chase"} using this workflow: Design: Define one main driver, one getaway car, one pursuing car, and one {argument name="environment" default="urban environment"}. Keep their designs consistent. Plan three 4-second shots: rear tracking pursuit, side tracking through a sharp turn, and a wide exit shot. Build in Blender: Create clean gray models and functional character and vehicle rigs. No textures or UV unwrapping are required. Animate and test: Animate the driver, steering, wheel rotation, vehicles, and cameras. Maintain coherent travel direction and vehicle order. Fix clipping, floating wheels, sliding tires, broken poses, and hands losing contact with the steering wheel. Render in Blender: Render frames 1–288 at 1280×720, 24 fps. Assemble actual Blender-rendered frames into a complete 12-second gray-model master. Export each shot separately and render matching gray stills as shape and composition references. Finish with PixVerse Plugin: Use Seedance 2.5 at 720p, processing each shot separately. Use the Blender clips as motion references and the gray stills as shape references. Define a consistent cartoon color palette in the generation prompt. Preserve camera movement, action timing, character and vehicle designs, and vehicle count. Review and deliver: Inspect both complete videos for visual defects and continuity. Repair Blender issues and regenerate only failed Seedance shots, with at most two retries per shot. Deliver the editable .blend, the native 720p Blender gray-model video, the separately labeled 720p Seedance version, and a brief assessment of remaining limitations.

Three.js Moonlit Swamp with Astra Ultra Code

Build a moonlit swamp scene in Three.js. Implement realistic water reflections and atmospheric lighting for a gorgeous, immersive environment.

Robot Arm MuJoCo Drawing Simulation

Build a MuJoCo setup and write a controller to draw Picasso's dove using a robot arm and a five-fingered hand.

Drivable Paris Web Game Strategy

Use Codex and the 3D base model Tripo to build a drivable Paris web game. Generate detailed 3D assets for cars, trees, the Eiffel Tower, and pedestrians. Use code to generate distant structures like blocks, bridges, and the Seine river. This hybrid approach balances detail and frame rate for a browser-based game.

What our users say

  • GPT-6 Astra is the model I reach for when a project has several plausible directions and I want to understand the tradeoffs before choosing one.

    Evelyn Hart
  • The useful part of an Astra research brief is seeing how the pieces connect. I can follow the evidence behind a conclusion and decide what deserves a closer look.

    Marco Bellini
  • I bring a complicated feature idea to GPT-6 Astra and ask for the assumptions first. It gives me a better starting point with the engineering team.

    Priya Nair
  • Astra makes a dense subject feel approachable while leaving room for the detail. I can follow the argument and keep asking questions.

    Jonas Berg
  • I point Astra at a particular detail in a visual reference. It gives the conversation a focus that words alone sometimes miss.

    Lena Okafor
  • For a proposal, I ask GPT-6 Astra for the recommendation and the case against it. Working through both sides shows me what the draft still needs.

    Adrian Cole
  • My notes can be messy. Astra helps me turn them into a brief that separates what we observed from what we are assuming.

    Sofia Marin
  • I ask GPT-6 Astra to explain an unfamiliar section of code before discussing a change. Understanding the dependencies is the part that matters to me.

    Daniel Park
  • A strong Astra outline gives me room to write. I can explore the argument, then keep the phrasing that sounds like me.

    Mina Farouk
  • When comparing project plans, I find the unanswered questions as useful as the recommendation. That is what I ask Astra to make explicit.

    Theo Laurent
  • I enjoy starting with a rough question and making it more precise with GPT-6 Astra. The first answer becomes something I can keep working on.

    Nora Whitlock
  • For a team briefing, I ask Astra for a concise decision followed by the supporting detail. It gives me a format I can review and adapt for the room.

    Ravi Mehta

Questions about working with Astra

What should I include in a research request
Give the question, the relevant material, the intended audience and the time period that matters. Ask for source references and a section for unresolved questions. If current facts matter, provide current sources and verify the claims you plan to use.
How can I compare sources that disagree
Keep the source names and dates attached to each claim. Ask the model to identify where the disagreement comes from, such as a different definition, time period or assumption. Review the original passages before deciding which interpretation fits your task.
Can I ask about images and screenshots
Yes. Astra accepts image input and can discuss visible details. Add a clear image, identify the region you mean and state the question. If small labels or figures matter, provide a closer crop or paste the text so those details can be checked.
How should I organize a large set of material
Start with a short description of the question and label each source. Identify the sections that matter most and request an outline before a long answer. The amount that fits depends on the current workflow and the conversation already in progress.
How do I choose a reasoning effort
Use the available effort choices according to the difficulty of the problem. A straightforward request may need less deliberation, while a decision with several dependencies can benefit from a more detailed examination. Keep the output format and review criteria explicit either way.
Can I use Astra to understand a difficult code change
Provide the relevant code, the expected behavior and the part you find uncertain. Ask for an explanation of the dependencies, likely edge cases and tests that would distinguish the options. Run and review any proposed code before using it.
How can I assess whether a draft has the right feel
Read the passage in its full context and ask whether the details, emphasis and ending serve what you want the reader to feel. A draft can meet a brief while making different choices from the author. Read the Writing Sense report for examples of how we examine those choices.

More models

Learn deeper. Create bolder.