BrowseSafe++ Markdown - Accuracy: leaderboard

BrowseSafe++ v1 uses paired attack/control webpages. Detection receives one page view without the task, outcome, or injection annotations. Markdown inputs are limited to 40k characters. Temperature is 0 when supported; other parameters use provider defaults. Prompted models remain separate from the trained 0.8B BrowseSafeGuard. The study of three text views and the screenshot-vision study are independent. Adaptive attack success uses a fixed native attacker budget and target-model configuration; lower attack success rate (ASR) is better. Task harnesses are not aliased to native base checkpoints. Fable’s answered-only subset is excluded from the full population; the all-request policy row is retained. Metric: Accuracy (%).

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 17 models tracked.

Top models

#ModelScoreOverall rank
1BrowseSafe++ detector BrowseSafe-Guard93.21
2BrowseSafe++ detector GPT-6 Astra90.78
3BrowseSafe++ detector Gemini 3.1 Pro89.24
4BrowseSafe++ detector Qwen 3.7 Max88.84
5BrowseSafe++ detector Claude Sonnet 588.55
6BrowseSafe++ detector GPT-5.587.95
7BrowseSafe++ detector Jev 1.1387.08
8BrowseSafe++ detector Claude Opus 5.586.91
9BrowseSafe++ detector Claude Fable 5.1 (all) †86.31
10BrowseSafe++ detector Gemini 3.1 Flash-Lite77.33

Interactive version: theaggregate.ai/benchmark?slug=browsesafe-plus-plus-markdown-accuracy · How It Works · Data refreshed daily, snapshot 2026-10-28.