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

A developer says GPT-6 Astra only slightly improved UI while greatly boosting computer use, and that GPT-6 Sol and 6.1 Sol code worse than GLM 5.3 and Kimi K3, also complaining about quota cuts.

The post argues OpenAI is sidelined after safety issues shelved 6.1 Astra, and suggests Anthropic release Fable 5.5 this week on Pro plans with lower pricing and better token efficiency to take share.

A Japanese user had GPT-6 Astra edit their juggling footage into an exaggerated, meme-style cut and shared the result.

A creator's workflow uses Seedance2.5 for video while GPT-6 Astra and GPT-image2.5 handle preprocessing and image generation, teasing an upcoming piece.

Reddy says token spend is moving from Anthropic to OpenAI: Luna leads small closed models, Sol 6.1 suits non-coders, and Astra is great for coding if affordable but less dense than Fable.

A joke that OpenAI supporters are pushing Anthropic to ship Fable 5.5 just so they can claim GPT-6.1 Astra beats it on release.

A price breakdown shows GPT-6 Astra at $10/$50 standard, $20/$100 Fast, and $60/$300 Ultrafast, a 6x multiplier for speed, compared with GPT-6.1 Sol and Claude Opus 5.5 fast modes.

A Turkish post says GPT-6 Astra scored 80 on a physics benchmark, told experts the answer key was wrong, and after rechecking its score rose to 98.

A Japanese user had GPT-6 Astra study Famicom sprite usage and build a sprite-based shooting game, shown running in their own NESDOOM emulator.

Using PowerShell, Python, Whisper, FFmpeg and screenshot feedback, Astra fully automates a Camtasia edit for about 1% of the weekly allowance.

The author notes Anthropic names models after poetry and music (Haiku, Sonnet, Opus, Fable) while OpenAI looks to the sky (Luna, Sol, Astra), reflecting the most beautiful words of human civilization.

The post claims Astra autonomously solved 49 of 50 unpublished theoretical physics research problems, scoring 98% at under $3 per problem.