ACE-Primus-Nemotron-70B-Instruct-nvfp4

Model Description

ACE-Primus-Nemotron-70B-Instruct-nvfp4 is a production-ready, enterprise-grade large language model developed through a collaborative effort between APMIC and Trend Micro’s cybersecurity AI research team.

This model is based on Llama-Primus-Nemotron-70B-Instruct, which itself builds upon NVIDIA’s Llama-3.1-Nemotron-70B-Instruct foundation and has been enhanced with cybersecurity-specific training and evaluation improvements. APMIC has contributed by performing NVIDIA NVFP4 precision quantization and hardware-aware engineering to support highly efficient inference across next-generation GPU platforms.

This release showcases APMIC’s capability to integrate third-party domain-specialized models into optimized deployment workflows tailored for modern enterprise AI environments.

Model Details

Developed by: APMIC
Funded by: APMIC, under the leadership of CEO Jerry Wu
Shared with / in collaboration with: Trend Micro / Trend-Cybertron team
Model type: Llama3ForConditionalGeneration (Transformers)
Language(s) (NLP): English (primary) with domain-specific cybersecurity terminology
License: LLAMA 3.1 Community License Agreement (via Trend-Cybertron initiative)
Finetuned from model: trend-cybertron/Llama-Primus-Nemotron-70B-Instruct

Base Model Background

The base model Llama-Primus-Nemotron-70B-Instruct was derived by applying continued pretraining and supervised finetuning on top of Llama-3.1-Nemotron-70B-Instruct, using extensive open cybersecurity text corpora and expert-curated instruction datasets. This process yields improvements in cybersecurity-oriented tasks, demonstrated by aggregate benchmark improvements over the original NVIDIA Nemotron benchmark baselines.

APMIC Optimization

NVFP4 Precision Quantization

APMIC’s contribution focuses on quantizing the model to NVIDIA NVFP4 precision and performing hardware-specific performance optimization.
NVFP4 quantization enables:

Substantial reductions in memory footprint and bandwidth requirements
Improved inference throughput on NVIDIA GPU architectures
Maintained quality across cybersecurity reasoning and instruction-following tasks
Production suitability for enterprise AI deployment

This work reflects APMIC’s expertise in precision-aware model optimization and deployment engineering tuned to infrastructure requirements.

Key Capabilities

Domain-Specialized Cybersecurity Reasoning

The original Primus-Nemotron model demonstrates enhanced performance in cybersecurity benchmarks compared to the NVIDIA baseline across multiple evaluation categories, highlighting:

Knowledge of cyber threat intelligence concepts
Structured reasoning over vulnerability and threat indicators
Improved relevance in domain-specific query responses

Enterprise-Ready Performance

With NVFP4 quantization and hardware optimization, this model is suitable for:

High-throughput inference in enterprise cybersecurity platforms
Integration into SOC (Security Operations Center) workflows
Scalable deployment on NVIDIA GPU infrastructure

Collaboration with Trend Micro

This release is the result of a strategic collaboration between APMIC and Trend Micro’s AI research team.
APMIC’s optimization complements Trend Micro’s domain-trained model, enabling joint delivery of: