Abliterated Large Flash

• 🧠 552B backbone params, 8B active in, 16B out
• 📏 Massive 1M-token context window
• 👁️ Natively multimodal — processes images and text
• 🔧 Function calling, web search, and agentic workflows
• 🔒 Abliterated: no content-filtering guardrails
• ⚡ fp8 quantization for fast, sparse inference

Abliteration AI

Abliteration AI is a Palo Alto company selling an OpenAI-compatible LLM API for work most assistants turn down: AI red teaming, cybersecurity, trust and safety, synthetic data and evals, ML research, and defense or government workflows. Its models start from…

Abliterated Large Flash takes DeepSeek V4.1 Flash as its backbone and applies abliteration — a weight-level technique that removes refusal behaviour — to produce an unrestricted multimodal assistant. The architecture is aggressively sparse: 552B total backbone parameters with only 8B active on input and 16B on output, which keeps throughput high despite the model's scale. Served at fp8, it pairs that efficiency with a one-million-token context window.

Within Abliteration AI's catalogue it occupies the speed-oriented, multimodal tier, sitting alongside Abliterated Large V2 in the Large family. Released in October 2026, it is the variant that natively ingests images as well as text, and it carries the full capability set users expect from a frontier-class base: reasoning, code generation, function calling, and web search.

The combination of huge context, vision input, and tool use makes it well suited to long-document and codebase analysis, agentic pipelines that mix screenshots or diagrams with text, and research workflows where guardrail refusals would otherwise interrupt the task. Users should expect no built-in content moderation and plan their own safeguards accordingly.