ZeroHour

Search: “Predator”

3 stories

GPT-5.6 Luna vs. GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review?

Entelligence benchmarks GPT-5.6 Luna ($1.20/M output) against GPT-6 Astra for code review: Luna found 69 verified bugs at 3.6% of Astra's cost.

Entelligence compared GPT-5.6 Luna ($0.20/$1.20 per million tokens) against GPT-6 Astra ($10/$50) on 50 benchmark pull requests from Cal.com, Sentry, Discourse, Keycloak, and Grafana. Astra verified 92 bugs versus Luna's 69, with precision of 96% versus 74%, and Astra caught 19 of 24 security bugs while Luna found only 9. Luna cost $0.20 total versus Astra's $5.66 and reviewed faster at 23 seconds versus 36, with the widest quality gap on Keycloak authentication and permission logic (6 vs 14 verified bugs). Running both models would find 82% of the 143 verified bugs for $5.86 total.

An AI CAPTCHA solver talked itself out of the right answer

Bern researchers solved rotation CAPTCHAs in 0.006 seconds with classical computer vision, while Gemini 3.1 Pro needed 67 seconds and overruled correct tool answers.

Researchers at Bern University of Applied Sciences built a script using 1970s circle-detection math and signal matching that solved rotation CAPTCHAs in 0.006 seconds, scoring 10/10 on real-world puzzles. Frontier models fared poorly: Gemini 3.1 Pro scored 7/10 taking 67 seconds, while GPT-4o and Grok scored 1/10. When given the script's correct answer as a tool, Gemini overruled it and lost a fifth of its score; models could verbally describe targets, such as identifying a cyan ring, but could not produce accurate click coordinates. The paper also notes these no-JavaScript CAPTCHAs reduce tracking, leaving only shape-matching tasks classical vision solves easily.

Help Net Security · 15d agoAI research1