GPT-6 Astra Is THE BEST Model so far (Worth the cost?)

Astra is OpenAI's first huge model in the GPT-6 line, and it's expensive. Input tokens cost $10 per million and output tokens cost $50 per million. That's about 2.5 times the price of GPT-5.6 Sol. The good news is it's part of the regular GPT plan with no extra charge, unlike Fable models. You choose when to use it.

The real question is whether the price is worth it. After a weekend of testing, the answer isn't simple. Astra shines on some tasks and falls flat on others. The biggest win was a 3D tower defense game made with a single prompt. It looked fun and the frost towers actually slowed enemies. Astra's 3D positioning and understanding of assets is clearly better than older models.

A Harry Potter broom ride test told a different story. The result was average, with a flimsy, clunky character. Kimi K3 and even GPT-5.6 Sol produced similar quality. A watch simulator result was also hit or miss. Astra does its job well sometimes, but other times it's just mediocre. Benchmark results from artificialanalysis.ai show Astra sometimes scores like GPT-5.6 Sol and sometimes much higher.

Guided projects are the sweet spot

The weekend project that impressed us most was a Chinese calligraphy tutor app. The idea was to use a camera to photograph calligraphy, analyze the grid, compare it to a database of master drawings, and give feedback like a tutor. GPT-5.6 struggled badly with detecting the page and finding characters. We hit errors for a whole weekend.

Astra solved the page boundary issue immediately. It fixed rotation problems, identified characters, and even used AI to find edges automatically. It showed a side-by-side comparison of the master's stroke and ours. We gave only three or four prompts and a few test examples. That's a real leap in problem-solving.

But Astra is not consistent across projects. Sometimes it solves the problem instantly. Other times it wanders and needs correction before it gets locked into a bad path. The lesson is clear: give Astra very clear examples and correct it fast when it starts to deviate. It's a powerful tool when guided well.

Early model, mixed results

Astra is the first super large model in the GPT-6 family. Larger models tend to be less consistent, and there hasn't been as much post-training as GPT-5.6 had. That explains the mixed performance. The model feels significantly improved, but the consistency isn't there yet. Maybe GPT-6.1 will fix that.

OpenAI support has been good. They reset usage twice because of the botched Astra rollout, which let us test more for free. That's worth noting.

Our take: use Astra when you're solving a new problem and have time to guide it. Expect great results sometimes and average results other times. For now, it's a high-risk, high-reward tool.