Claude Opus 4.7 FAILS Real-World Tests: Token Rationing, Compute Shortages & Degraded AI

Anthropic launched Claude Opus 4.7 with strong benchmark numbers in coding and vision, but independent developers quickly discovered it performs worse than Opus 4.6 in real-world tasks — especially when using the casual, ambiguous prompts that worked fine on the previous model. The culprit isn't a design flaw; it's token rationing. As Anthropic faces the same compute shortage that already degraded OpenAI's models (ChatGPT-4 remains the peak, with every version since declining in quality), the new 4.7 dynamically limits reasoning tokens, burning budgets faster and producing rushed or incomplete outputs for vague prompts. This is the moment to understand two things: first, vague prompting was never good — detailed, paragraph-length prompts always produce better results; and second, AI progress is not linear, new does not mean better, and the supply of compute is not keeping pace with demand. Here's what changed, why it happened, and which models are actually cost-effective right now.

Watch Author Update Live at 4pm (Central) on Fridays:
https://www.youtube.com/@Author-Update

Support us on Patreon:
https://www.patreon.com/novelmarketing

Novel Marketing Channel:
https://www.youtube.com/@Novel-Marketing

Author Arsenal Channel:
https://www.youtube.com/@Author-Arsenal

Patron Toolbox:
https://www.authormedia.com/patron-toolbox/

Hosted by Thomas Umstattd Jr. and Jonathan Shuerger. Subscribe for weekly publishing industry analysis, author marketing strategies, and tech insights you can actually use. Visit AuthorMedia.com for show notes, tools, and resources.

#AuthorTube #PublishingNews #AINews

Видео Claude Opus 4.7 FAILS Real-World Tests: Token Rationing, Compute Shortages & Degraded AI канала Author Update