OrionLLM/GRM-3.2-Turf

🤗 Hugging Face 来源text-generationapache-2.01.2B 参数2.3 GBsafetensors✓ 2 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo OrionLLM/GRM-3.2-Turf ./model-folder
需要做种者 →

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

GRM-3.2-Turf LFM2.5-1.2B-Thinking Qwen3.5-2B Gemma-4-E2B
Knowledge & STEM
Multidisciplinary knowledgeMMLU-Pro 56.2 49.65 66.5 60.0
Scientific reasoningGPQA Diamond 42.4 37.86 51.6 43.4
Instruction Following & Function Calling
Instruction followingIFEval 91.2 88.42 78.6 —
Complex instruction followingIFBench 46.8 44.85 41.3 —
Function callingBFCL v3 59.3 56.97 — —

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.

Model Domain
Sky35B-A3B Flagship model for long-horizon tasks
Cliff9B Capable model for low GPU environments
Turf1.2B Lightweight model for practical reasoning

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.


GRM-3.2-Turf is developed by OrionLLM and released under the Apache 2.0 License.