---
license: apache-2.0
base_model:
- rico03/Qwen3.6-27B-Claude-Opus-Reasoning-Distilled
- OrionLLM/GRM-2.6-Plus
base_model_relation: merge
pipeline_tag: image-text-to-text
---

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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.

### Detailed Benchmarks

<table>
	<tr>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">Benchmark</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">GRM-2.6-Opus</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">GRM-2.6-Plus</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">Qwen3.6-27B</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">google/gemma-4-31B-it</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">GPT-5.4-Mini</th>
		<th style="background: rgba(128,128,128,0.1); text-align: center;">Claude-4.5-Haiku</th>
	</tr>
	<tr>
		<td align="center" colspan="7" style="background: linear-gradient(90deg, rgba(124,58,237,0.45) 0%, rgba(99,102,241,0.42) 50%, rgba(59,130,246,0.45) 100%); font-weight: bold; height:32px; padding-top:2px; padding-bottom:2px;"><i>Knowledge &amp; STEM</i></td>
	</tr>
	<tr>
		<td align="center">GPQA Diamond</td>
		<td align="center"><b>89.2</b></td>
		<td align="center">88.3</td>
		<td align="center">87.8</td>
		<td align="center">84.3</td>
		<td align="center">88.0</td>
		<td align="center">73.0</td>
	</tr>
</table>

---

<div align="center">
  
**GRM-2.6-Opus** is developed by **[OrionLLM](https://huggingface.co/OrionLLM)** and released under the Apache 2.0 License.

</div>