GPT-6 Astra in Practice: Tests, Use Cases, and Feedback

A Japanese user asked GPT-6 Astra for a 3D terrain map, and it combined PLATEAU, base map data and aerial photos to build a Blender base for placing models.

A long post breaks down five mechanism issues four days after Astra's launch: dual context pricing, effort tiers, the approval line, invisible chain-of-thought, and the Codex stop hook.

A video shows Astra over-reasoning in response to a simple greeting, an early hands-on clip played for laughs.

A creator used GPT-6 Astra to rewrite the prompts and remake the "Chibiti-chan VS Seiryu" character battle video.

One person running GPT-6 Astra in Codex on a personal Pro account at about $20k a day out of pocket had the account downgraded to Free with no notice, and Codex stopped mid-task with an error.

Meshy's founder says Astra is good at understanding coarse structure, but precise reproduction is a different problem, so the two are complementary rather than replacements.

The author claims most people use only 10% of Astra's capability and that the difference lies in prompting, linking to a full prompting masterclass article.

A user jokes that Codex's quality drop is now concrete: GPT-6 Astra can't even draw a pelican on a bicycle, and this is in Ultra mode.

The author compares ChatGPT, Claude and Gemini usage, arguing models should be chosen by the depth, speed and cost a task needs, so the high-performance Astra isn't required at every stage.

A satirical meme: while everyone is discussing AI getting dangerous, OpenAI will, two months from now, release another version as usual, GPT-6.1 Astra.

The author says one image plus one agent can generate a complete 3D scene, calling the combination of GPT-6 Astra and HYPER3D MCP a wild pairing.

A Japanese developer partly used Astra to build an MCP bridge tool linking Blender and Substance Painter, stressing that you shouldn't hand all the work to AI.