Fable 5.1

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.

Anthropic Fable 5.1 System Prompt Fully Leaked Hours After Launch Exposing 275000 Characters of Rules

Anthropic released its flagship Fable 5.1 model alongside Mythos 5.1 on September 2, achieving strong benchmark scores including 90 percent on ARC-AGI-2. Within hours, researcher Pliny the Liberator published the complete 275000-character system prompt on GitHub, far exceeding the company's official 27000-word disclosure. The leaked document details 46 built-in tools, strict copyright restrictions, memory classification boundaries, and behavioral constraints that function as an internal employee handbook. The incident highlights that model weights remain the true core while prompt-based guardrails create an attack surface once mapped. It also reveals privacy rules that permanently exclude storage of minor identities, criminal records, and self-harm indicators even when users disclose them. The leak underscores the growing gap between vendor transparency claims and actual runtime instructions governing frontier AI systems.