This is a GGUF format version converted from the Qwen3-VL-30B-A3B-Instruct model, specifically optimized for llama.cpp. This model is a multimodal visual language model with 30 billion parameters, supporting image understanding and text generation tasks.

MultimodalGguf

This is a quantized version of the Huihui Qwen3-VL-8B thinking ablated model. Based on the Qwen3-VL-8B architecture, it is specifically optimized and quantized for image-text conversion tasks and can be efficiently run through the llama.cpp tool.

MultimodalGguf

The quantized version of the Huihui Qwen3-VL-4B thinking elimination model, optimized based on the Qwen3-VL-4B model, is specifically designed to eliminate the thinking chain reasoning process and can be used with the latest llama.cpp to provide efficient image-text to text processing capabilities.

MultimodalGguf

The Chandra-OCR quantized model is a version after quantizing the original Chandra model. It is specifically designed for image-to-text tasks and can be used with the latest llama.cpp.

Computer VisionGguf

This is a llama.cpp quantized version based on the TheDrummer/Rivermind-24B-v1 model. It uses imatrix technology for optimized quantization and provides multiple quantization levels to adapt to different hardware configurations, enabling efficient operation in various environments.

Natural Language ProcessingGguf

This model is a text generation model fine-tuned based on Meta's Llama-3.1 architecture. It is trained using reinforcement learning with the TRL library and the GRPO (Group Relative Policy Optimization) method, and is specifically optimized for argument generation tasks.

Natural Language ProcessingTransformers

This is the GGUF quantized version of NVIDIA's Qwen3-Nemotron-32B-RLBFF large language model. It uses the llama.cpp tool for multi-precision quantization, offering more than 20 quantization options from BF16 to IQ2_XXS, suitable for different hardware configurations and performance requirements.

Natural Language ProcessingGguf

This project is a llama.cpp GGUF quantized version based on the Qwen3-VL-32B-Instruct model, offering various quantization types to meet different hardware and performance requirements. Quantization is performed using a specific dataset in combination with the imatrix option to ensure quantization quality. It supports online weight repackaging to improve the performance of ARM and AVX machines.

MultimodalGguf

This is the Llamacpp imatrix quantized version of the Qwen3-VL-2B-Thinking model, providing files of various quantization types that can run efficiently in different hardware environments. This model is a multimodal vision-language model with 2B parameters and has the ability of chain-of-thought reasoning.

MultimodalGguf

This is a quantized version of the Qwen3-VL-2B-Instruct model. The llama.cpp tool and the imatrix method are used to generate model files with multiple quantization levels, which are convenient for efficient operation in different hardware environments. This model is a multimodal vision-language model with 2B parameters, supporting the interaction between images and text.

MultimodalGguf

This project quantizes the MiniMax-M2 model of MiniMaxAI. Using the llama.cpp tool, it provides model files of multiple quantization types for users with different needs, facilitating the efficient operation of the model under different hardware conditions.

Natural Language ProcessingGguf

JanusCoderV-7B is a 7B parameter code generation model developed by InternLM. This project provides multiple versions of imatrix quantization using llama.cpp, supporting various quantization levels to meet different hardware requirements.

Natural Language ProcessingGguf

This is a quantized version of the internlm's JanusCoder-14B model. It is quantized using specific tools and datasets, providing a variety of quantization type files from low quality to high quality. It can run in LM Studio or projects based on llama.cpp.

Natural Language ProcessingGguf

This is a quantized version of the internlm's JanusCoder-8B model, using the imatrix quantization technology of llama.cpp. It significantly reduces the storage and computational resource requirements of the model while ensuring performance, enabling the model to run efficiently on more devices.

Natural Language ProcessingGguf

This is the MXFP4_MOE quantized version of the MiniMax-M2 model. It is re-quantized based on the version with the chat template fixed by unsloth, enabling more efficient use of the MiniMax-M2 model's capabilities in specific scenarios. This is a coding model that needs to be used with the latest llama.cpp.

Natural Language ProcessingGguf

MiniMax-M2 is a large language model built on an experimental branch of llama.cpp. It has a mixture of experts architecture and supports efficient text generation and inference tasks. This model requires a specific experimental branch to run properly.

Natural Language ProcessingTransformers

Wraith-8B is the first model in the VANTA Research entity series, fine-tuned based on Meta's Llama 3.1 8B Instruct. This model performs excellently in mathematical reasoning, achieving an accuracy rate of 70% in the GSM8K benchmark test. It also has a unique cosmic intelligence perspective, providing strong support for various application scenarios.

Natural Language ProcessingTransformersEnglish

Qwen3-Next-80B-A3B-Thinking is a quantized version based on the Qwen3-Next-80B-A3B-Thinking model, specifically optimized for text generation tasks. This model needs to be used in conjunction with version PR 16095 of llama.cpp and offers multiple quantization levels to adapt to different hardware configurations.

Natural Language ProcessingGguf

Llama-4-Maverick-17B-128E-Instruct-NVFP4 is a multilingual large language model that has undergone FP4 quantization processing. It is based on the Meta-Llama-3.1 architecture and is specifically designed for business and research purposes. By quantizing the weights and activations to the FP4 data type, this model significantly reduces the disk space and GPU memory requirements while maintaining good performance.

Natural Language ProcessingSafetensorsMultiple Languages

This is an MXFP4 quantized experimental version of Qwen3-Next-80B-A3B-Instruct, developed based on cutting-edge quantization technology, providing efficient text generation capabilities. This version is experimental and requires a special version of llama.cpp support.

Natural Language ProcessingGguf