# Precision adaptation

Qwen2.5-7B-Instruct is an instruction-tuned model based on Qwen2.5-7B, optimized for text generation tasks, especially in chat scenarios.

Ultra-low-bit quantization (1-2 bit) model using IQ-DynamicGate technology, suitable for memory-constrained devices and efficient inference scenarios

Llama-3.2-3B-Instruct GGUF is a 3B-parameter large language model released by Meta, utilizing IQ-DynamicGate technology for ultra-low-bit quantization (1-2 bits), optimizing inference performance while maintaining memory efficiency.

GLM-Z1-32B-0414 is a 32B-parameter multilingual text generation model supporting Chinese and English, released under the MIT license.

Ultra-low-bit quantization (1-2 bits) model using IQ-DynamicGate technology, suitable for memory-constrained devices and edge computing scenarios

A model fine-tuned based on Meta Llama-3.1-70B-Instruct, optimized with NVIDIA HelpSteer2 dataset, supporting text generation tasks.

An instruction-tuned model based on OLMo-2-0325-32B-DPO, utilizing IQ-DynamicGate ultra-low bit quantization technology, optimized for memory-constrained environments.

A 49B-parameter large language model utilizing IQ-DynamicGate ultra-low-bit quantization technology, supporting 1-2 bit precision-adaptive quantization, optimized for memory efficiency and inference speed

IBM Granite series 8B parameter instruction-tuned language model, employing IQ-DynamicGate ultra-low-bit quantization technology, suitable for efficient inference scenarios

This is an instruction-tuned model based on Mistral-Small-3.1-24B-Base-2503, utilizing GGUF format and IQ-DynamicGate ultra-low bit quantization technology.

Qwen2.5-7B-Instruct-1M is an instruction-tuned version based on Qwen2.5-7B, employing IQ-DynamicGate ultra-low-bit quantization (1-2 bits), suitable for efficient inference in memory-constrained environments.

Qwen2.5-14B-Instruct-1M is an instruction-tuned model based on Qwen2.5-14B, supporting text generation tasks and suitable for chat scenarios.

An IQ-DynamicGate ultra-low-bit quantization (1-2 bit) model based on Llama-3-8B-Instruct, utilizing precision-adaptive quantization technology to enhance inference accuracy while maintaining extreme memory efficiency.

Mistral-7B-Instruct-v0.1 is a fine-tuned model based on Mistral-7B-v0.1, supporting text generation tasks. It employs IQ-DynamicGate ultra-low bit quantization technology, making it suitable for memory-constrained deployment environments.