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license: apache-2.0
base_model:
- LiquidAI/LFM2.5-1.2B-Thinking
pipeline_tag: image-text-to-text
---
<p align="center">
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<div align="center">
<a href="https://huggingface.co/OrionLLM/GRM-3.2-Turf/" style="text-decoration: none;">
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## 1. Introduction
We're introducing **GRM-3.2-Turf**, our lightweight model built for **difficult reasoning problems** and **general conversation** in local environments. GRM-3.2-Turf marks a substantial leap over its predecessor, **GRM-2.6-Air-Opus**, and is designed to serve as a dependable engine for low-resource devices with low processing power.
The model is purpose-built to deliver efficient execution without sacrificing structured reasoning capability, making it ideal for mobile devices, embedded systems, and local deployments where memory and compute constraints are critical.
## 2. Key Capabilities
- **On-Device Efficiency:** Engineered to run smoothly on low-resource hardware with minimal memory footprint and fast inference latency.
- **Enhanced Local Reasoning:** Substantial leap over GRM-2.6-Air-Opus in structured reasoning, problem-solving, and general conversation tasks.
- **High-Fidelity Instruction Following:** Exceptional capability in handling constrained prompts, complex system instructions, and precise response formatting.
- **Robust Tool Use:** Strong performance in tool calling and function execution, enabling agentic workflows in lightweight environments.
## 3. Performance
GRM-3.2-Turf is designed as our premier lightweight model for local execution. It builds directly on the strengths of GRM-2.6-Air-Opus while setting new benchmarks for sub-2B reasoning and instruction-following capability on edge hardware.
### Detailed Benchmarks
<table>
<tr>
<th style="background: rgba(128,128,128,0.1); text-align: center;"> </th>
<th style="background: rgba(128,128,128,0.1); text-align: center;">GRM-3.2-Turf</th>
<th style="background: rgba(128,128,128,0.1); text-align: center;">LFM2.5-1.2B-Thinking</th>
</tr>
<tr>
<td align="center" colspan="3" 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 & STEM</i></td>
</tr>
<tr>
<td align="center">MMLU-Pro</td>
<td align="center"><b>56.2</b></td>
<td align="center">49.65</td>
</tr>
<tr>
<td align="center">GPQA Diamond</td>
<td align="center"><b>42.4</b></td>
<td align="center">37.86</td>
</tr>
<tr>
<td align="center" colspan="3" 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>Instruction Following & Function Calling</i></td>
</tr>
<tr>
<td align="center">IFEval</td>
<td align="center"><b>91.2</b></td>
<td align="center">88.42</td>
</tr>
<tr>
<td align="center">IFBench</td>
<td align="center"><b>46.8</b></td>
<td align="center">44.85</td>
</tr>
<tr>
<td align="center">BFCL v3</td>
<td align="center"><b>59.3</b></td>
<td align="center">56.97</td>
</tr>
</table>
*Scores are taken from each provider's own published model card, blog post, or evaluation benchmark suite.*
## 4. Family
The GRM-3.2 family is available in various sizes to suit every use case.
<table>
<tr>
<th style="background: rgba(128,128,128,0.1); text-align: center;">Model</th>
<th style="background: rgba(128,128,128,0.1); text-align: center;">Size</th>
<th style="background: rgba(128,128,128,0.1); text-align: center;">Domain</th>
</tr>
<tr>
<td align="center">GRM-3.2-Sky</td>
<td align="center">35B-A3B</td>
<td align="center">Flagship model for long-horizon tasks</td>
</tr>
<tr>
<td align="center">GRM-3.2-Cliff</td>
<td align="center">9B</td>
<td align="center">Capable model for low GPU environments</td>
</tr>
<tr>
<td align="center"><b>GRM-3.2-Turf</b></td>
<td align="center"><b>1.2B</b></td>
<td align="center"><b>Lightweight model for low-resource devices</b></td>
</tr>
</table>
## 5. Architecture
GRM-3.2-Turf is built on the **LiquidAI/LFM2.5-1.2B-Thinking** base architecture, a 1.2B-parameter model optimized for reasoning, general conversation, and tool use, specifically tailored for efficient deployment on resource-constrained hardware.
---
<div align="center">
**GRM-3.2-Turf** is developed by **[OrionLLM](https://huggingface.co/OrionLLM)** and released under the Apache 2.0 License.
</div> |