# Ultra-low-bit quantization

Qwen3-30B-A3B is a large language model based on Qwen3-30B-A3B-Base, supporting text generation tasks, optimized for memory efficiency with ultra-low-bit quantization technology.

Qwen3-14B is a GGUF format model generated from Qwen/Qwen3-14B-Base, supporting text generation tasks and optimized for memory efficiency using IQ-DynamicGate ultra-low-bit quantization technology.

GLM-Z1-9B-0414 is a bilingual text generation model supporting both Chinese and English, utilizing the GGUF format and suitable for various quantization levels, from BF16 to ultra-low-bit quantization (1-2 bits).

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.

Ultra-low-bit quantization (1-2 bits) language model using IQ-DynamicGate technology, suitable for memory-constrained environments

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

Ultra-low-bit quantization (1-2 bit) large language model using IQ-DynamicGate technology, supporting multilingual text generation tasks

An ultra-low-bit (1-2 bit) quantized model based on Llama-3.1-70B, utilizing IQ-DynamicGate technology for adaptive precision quantization, enhancing accuracy while maintaining memory efficiency.

OlympicCoder-32B is a code generation model based on Qwen2.5-Coder-32B-Instruct, employing IQ-DynamicGate ultra-low-bit quantization technology for efficient inference in 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

GGUF quantized version of Gemma 3 with 27B parameters, supporting image-text interaction tasks

EXAONE-Deep-32B is a 32B-parameter large language model supporting English and Korean, specifically designed for text generation tasks.

A 7.8B-parameter model featuring ultra-low-bit quantization (1-2 bits) using IQ-DynamicGate technology, supporting English and Korean text generation tasks.

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

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.

Llama-3.1-8B-Instruct is an instruction-tuned version based on Llama-3-8B, utilizing IQ-DynamicGate technology for ultra-low-bit quantization (1-2 bits), enhancing accuracy while maintaining memory efficiency.