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1. Introduction

GRM-2.6-Opus is a merge between OrionLLM/GRM-2.6-Plus and rico03/Qwen3.6-27B-Claude-Opus-Reasoning-Distilled.

GRM-2.6-Opus is a general-purpose AI model optimized for difficult, high-complexity tasks. It is designed to deliver stronger performance for its size while remaining practical, efficient, and accessible for advanced local and research-oriented use.

The model now follows an Opus-style reasoning format, producing more structured, organized, and deliberate reasoning. This merge improves its ability to handle terminal agents, coding workflows, and complex problem-solving tasks, taking advantage of the strong reasoning and agentic capabilities associated with Claude Opus-style distilled behavior.

GRM-2.6-Opus demonstrates improvements over the original GRM-2.6-Plus, especially in structured reasoning, coding, agent workflows, and high-difficulty STEM evaluation.

2. Key Capabilities

Opus-Style Structured Reasoning: GRM-2.6-Opus uses a more organized reasoning format, helping it produce clearer and more reliable solutions for complex tasks.
Improved Terminal Agent Ability: The model is better suited for terminal-based agents, tool-style workflows, debugging, code execution planning, and multi-step technical tasks.
Stronger Coding Performance: The merge improves code reasoning, implementation planning, and difficult programming task handling.
Enhanced General-Purpose Intelligence: GRM-2.6-Opus remains useful across research, STEM, chat, coding, local agents, and advanced problem-solving.
Improved Over GRM-2.6-Plus: The model builds on the original GRM-2.6-Plus and adds stronger structured reasoning behavior through the Opus-style distilled merge.

3. Performance

GRM-2.6-Opus is designed to be a highly capable 27B local AI model for complex reasoning, coding, everyday chat, and agentic workflows. It focuses on delivering better performance for its size, making it a strong option for users who want powerful reasoning without relying only on massive-scale models.

Its core strength is practical intelligence: structured reasoning, strong task understanding, improved coding behavior, stable responses, and the ability to handle difficult problems across multiple domains.