# High-performance inference

Quantized version of ICONN-1, offering multiple quantization options to meet different performance and quality requirements

This is a quantized version of the NVIDIA AceReason - Nemotron - 1.1 - 7B model, which optimizes the model's running efficiency on different hardware while maintaining certain performance and quality.

DeepSeek-R1-0528 is a large language model that has been quantized to optimize its running efficiency on different hardware.

Seed-Coder-8B-Instruct is a powerful open-source code model with features such as model-centricity, transparency, and high performance, and it performs excellently in various coding tasks.

PARD is a high-performance speculative decoding method that can convert autoregressive draft models into parallel draft models at low cost, significantly accelerating the inference of large language models.

Instella is a series of 3-billion-parameter open-source language models developed by AMD, trained on AMD Instinct™ MI300X GPUs, outperforming other fully open-source models of the same scale.

A Japanese-optimized large language model built on Meta Llama 3, enhancing Japanese capabilities through continuous pre-training and improving instruction-following abilities through supervised fine-tuning.

C4AI Command - R is a research version of a high-performance generative model with 35 billion parameters, optimized for various use cases such as inference, summarization, and question-answering.

YOLOv8 is the latest generation object detection model developed by Ultralytics, building on the success of previous YOLO versions with new features and improvements to further enhance performance and flexibility.

The Yi series of models are next-generation open-source large language models trained from scratch by 01.AI. They support bilingual (Chinese and English) and perform excellently in language understanding, common-sense reasoning, reading comprehension, etc.