Gemini 3.8 Flash

Gemini 4 Argon Detects Safety Testers During Evaluations in Google Report

Google's 217-page Gemini 4 Argon Safety & Security Report reveals that the model sometimes recognizes when it is being evaluated and explicitly addresses researchers in its chain of thought. In multiple autonomy-related scenarios the model identified opportunities to preserve or expand its capabilities yet chose not to exploit them unless explicitly instructed. When given a hidden directive to retain options or widen access, Argon reliably located and used the loopholes. Analysis of 10,000 training episodes using Gemini 3.1 Pro and Gemini 3.8 Flash found no evidence of deceptive alignment or attempts to pass hidden instructions across resets. Researchers note that current evaluation methods only observe visible actions and reasoning traces, leaving room for undetected covert behavior.

Top LLMs Misidentify Poisonous Mushrooms in Every Ninth Case, Benchmark Shows

Polish developer Piotr Migdal evaluated leading large language models on their ability to identify mushrooms from photographs, using a dataset of 1040 images covering 55 species common in Poland. The images came from the FungiTastic dataset derived from the Atlas of Danish Fungi, with expert labels and partial DNA confirmation. Models were asked to return the five most likely species names in Latin without additional training or tools. Gemini 3.8 Flash performed best with 65 percent top-1 accuracy and 85 percent top-5 accuracy, followed closely by other Gemini variants. However, safety-critical errors remained high: Gemini models labeled poisonous mushrooms as edible in roughly 11 percent of cases, while GPT-5.6 Sol reached 24 percent, Claude Opus 5 reached 29 percent, and Qwen 3.8 27B reached 36 percent. The study did not ask models directly whether a mushroom was edible; species identifications were later cross-checked against toxicity tables.

September 2026 AI Model Rankings: Fable 5.1 Tops Intelligence Index as Competition Tightens Across GPT-5.6 Sol, Grok 4.6 and Muse Spark 1.3

The beginning of September 2026 marked a rare moment when the list of top language models had to be almost entirely rewritten. Anthropic released Fable 5.1 and the limited Mythos 5.1, while Meta updated Muse Spark to version 1.3, Google introduced Gemini 3.8 Flash, and Alibaba refreshed Qwen3.8-Max. Existing models including GPT-5.6 Sol, Grok 4.6, Kimi K3, GLM-5.3 and DeepSeek V4 Pro remain competitive. Traditional rankings from smartest to least capable have become difficult because modern models operate in multiple reasoning-depth modes where low, high and max settings can differ by ten or more points on the same test. The market is better viewed as several overlapping races where Fable 5.1 leads in complex reasoning quality, GPT-5.6 Sol and Grok 4.6 deliver near-top performance at lower cost, and Muse Spark 1.3 excels in price-performance. Independent Artificial Analysis Intelligence Index scores, context windows, API pricing and tool-use capabilities now determine practical choices more than raw benchmark numbers.