ASI:One Extended | ASI:One Documentation

Advanced Reasoning for Web3 & Agentic Applications

Introduction

ASI:One Extended is our most capable compact reasoning model, designed with the Web3 community in mind. It delivers exceptional multi-step reasoning and transparent decision traces—while still running on commodity hardware.

Performance Snapshot

Metric	ASI:One Extended
MMLU Benchmark	89 %
Context Window	64 k tokens

_{Scores surpass many larger publicly-reported LLMs.}

Why ASI:One Extended?

Superior Multi-Step Problem Solving

Breaks complex tasks into logical steps, with intermediate validations that slot neatly into on-chain pipelines.

Enhanced Decision-Making

Evaluates multiple solution paths via explicit reasoning traces—perfect for collaborative debugging and policy checks.

Adaptable to Ambiguous Instructions

Builds probabilistic intent graphs and asks clarifying questions, reducing mis-alignment in sparse specs.

Improved Self-Correction

Sanity checks intermediate outputs against domain constraints, rolling back and retrying when needed.

Reliable Agentic Behaviour

Hierarchical planning allocates subtasks to specialised agents and reprioritises steps in real time.

Higher Performance Ceiling

Layered cognition refines hypotheses between iterations—unlocking continual improvements without retraining from scratch.

Trustworthiness & Safety

Capability	Detail
Transparent Reasoning Paths	Every conclusion ships with hashed reasoning steps for audit and on-chain anchoring.
Reduced Hallucination Risk	Confidence thresholds & cross-checks keep outputs grounded in verifiable data.
Consistency Checking	Constraint solvers validate logic against formal specs, flagging discrepancies early.
Security-First Approach	Highlights privilege-escalation & re-entrancy risks, suggesting mitigation steps.

Ready to explore? Jump to the Chat Completion quick-start and set model:"asi1-extended" to experience deeper reasoning with transparent traces.