This is a quantized version of TheDrummer's Magidonia-24B-v4.3 large language model. By using the imatrix quantization technology of llama.cpp, GGUF format files with various precisions from BF16 to IQ2_XS are generated, aiming to run the model more efficiently under different hardware conditions (especially in resource-constrained environments) while maintaining the model performance as much as possible.

Natural Language ProcessingGguf

This project is a quantized version of TheDrummer's Cydonia-24B-v4.3 model. It uses llama.cpp for quantization processing, aiming to provide model files of different quantization types to meet the needs of different hardware and performance. It is a large language model with 24B parameters, mainly used for text generation tasks.

Natural Language ProcessingGguf

This is the GGUF quantized version of the large language model Mistral-Large-3-675B-Instruct-2512 developed by Mistral AI. The original model has 675 billion parameters and is designed for instruction-following tasks. This project uses the llama.cpp tool and combines it with the imatrix calibration dataset to generate more than 20 different precision quantized model files from Q8_0 to IQ1_S, aiming to balance model performance, inference speed, and storage/memory usage, enabling it to run on a wider range of hardware.

Natural Language ProcessingGgufMultiple Languages

Hito 1.7B is a GGUF quantized version model optimized for tools such as llama.cpp, Ollama, and LM Studio. It has 1.7 billion parameters and uses the Nested Cognitive Reasoning (NCR) method, enabling a structured and self-correcting thinking mode to improve the accuracy and transparency of reasoning.

Natural Language ProcessingGgufEnglish

This project provides a text generation model fine-tuned based on the Microsoft Phi-3.5-mini-instruct model, which has been converted to the GGUF format and is suitable for the llama.cpp inference framework. The model was fine-tuned on the philschmid/guanaco-sharegpt-style dataset, optimizing its instruction-following and dialogue capabilities, and is suitable for efficient text generation tasks in resource-constrained environments.

Natural Language ProcessingGguf

This is a quantized version of the Microsoft Fara-7B model, optimized using the imatrix technology of llama.cpp. The model supports multiple quantization levels, from high-precision bf16 to extremely low-precision IQ2_M, meeting the needs of different hardware configurations and performance requirements.

Natural Language ProcessingGguf

This is the GGUF quantized version of ArliAI's GLM-4.5-Air-Derestricted model. It uses llama.cpp and imatrix technology for optimized quantization processing, offering multiple quantization levels to suit different hardware configurations and performance requirements.

Natural Language ProcessingGguf

This is a quantized version of the squ11z1's Hypnos-i1-8B model, which is quantized using the llama.cpp tool and a specific dataset. The model is based on the Llama-3 architecture, offering multiple quantization type options and supporting text generation tasks. It is suitable for various application scenarios such as inference and dialogue.

Natural Language ProcessingGgufEnglish

This is a quantized version of TheDrummer's Snowpiercer-15B-v4 model, quantized using llama.cpp and imatrix technology. This version offers multiple quantization levels from BF16 to IQ2_S, meeting the needs of users with different hardware conditions and performance requirements. The model is calibrated and optimized using a specific dataset and supports the online repackaging function to improve performance on ARM and AVX hardware.

Natural Language ProcessingGguf

This is a quantized version of ai-sage's GigaChat3-10B-A1.8B model, using the imatrix quantization technology of llama.cpp, which can run more efficiently under different hardware conditions. The model supports Russian and English and is mainly used for text generation tasks.

Natural Language ProcessingGgufMultiple Languages

This is the GGUF quantized version of allenai's Olmo-3-32B-Think model. It undergoes various quantization processes using the llama.cpp tool, aiming to enhance the model's performance and efficiency in specific environments. It offers multiple quantization options from Q2 to Q8 to meet different hardware configurations and performance requirements.

Natural Language ProcessingGgufEnglish

This is the quantized version of kldzj's GPT-OSS-120B-Heretic-v2 model, which is quantized using the imatrix technology of llama.cpp. The model significantly reduces the storage and computing resource requirements through quantization technology while maintaining good model performance, facilitating deployment and operation on various devices.

Natural Language ProcessingGguf

This is the quantized version of the ai-sage/GigaChat3-10B-A1.8B model, using the GGUF format and requiring support from a specific llama.cpp branch. The model adopts a Mixture of Experts architecture, with a total of approximately 11.8 billion parameters, of which approximately 1.8 billion are activated parameters.

Natural Language ProcessingGgufMultiple Languages

This is a quantized version of the VibeStudio MiniMax-M2-THRIFT model, generated using the llama.cpp tool and a specific dataset. It provides GGUF files of various quantization types and supports running in LM Studio or projects based on llama.cpp.

Natural Language ProcessingGguf

This is a large language model with 172B parameters obtained by uniformly pruning 25% of the experts in MiniMax-M2 using the REAP method. It has been optimized and quantized specifically for llama.cpp, supporting multiple quantization levels and can run in LM Studio or projects based on llama.cpp.

Natural Language ProcessingGgufEnglish

This is a large language model with 139B parameters obtained by uniformly pruning 40% of the experts in MiniMax-M2 using the REAP method. It adopts the GLM architecture and Mixture of Experts (MoE) technology, and undergoes various quantization processes through llama.cpp, suitable for text generation tasks.

Natural Language ProcessingGgufEnglish

This is a quantized version of the Qwen3-4B-Instruct-2507-heretic model. Multiple quantization types of model files are generated using the llama.cpp tool and the imatrix dataset, which can run in various environments and provide users with more options.

Natural Language ProcessingGguf

This is a quantized version of the Llama-3.1-8B-Instruct-heretic model released by p-e-w, using the llama.cpp b7049 version for imatrix quantization. It provides multiple quantization options to meet different hardware and performance requirements and supports running in LM Studio or llama.cpp.

Natural Language ProcessingGgufMultiple Languages

This is a quantized version of the p-e-w/gpt-oss-20b-heretic model, quantized using the imatrix technology of llama.cpp. The model is a large language model with 20 billion parameters, offering a variety of quantization options ranging from high quality to low quality, with file sizes from 41.86GB to 11.52GB, suitable for different hardware conditions.

Natural Language ProcessingGguf

This is the llama.cpp quantized version of the Precog-123B-v1 model, which provides a variety of quantization types to meet the needs of different hardware configurations and usage scenarios. This model is a large language model with 123 billion parameters and can run efficiently on various hardware after optimization.

Natural Language ProcessingGguf