This model is a GGUF format model generated by in-depth fine-tuning of the Qwen3-Coder-30B-A3B-Instruct Mixture of Experts model using Brainstorm 20x technology. It is designed for programming and general purposes, supports a 256K long context, and is optimized for code generation and understanding of mainstream and niche programming languages.

Natural Language ProcessingGgufMultiple Languages

This is the GGUF quantized version of the Qwen/Qwen3-Coder-30B-A3B-Instruct language model, specifically optimized for code generation and programming tasks. It is converted using FP32 precision and is suitable for local inference deployment.

Natural Language ProcessingGgufMultiple Languages

Qwen3-Coder-REAP-363B-A35B is a sparse mixture-of-experts model obtained by pruning 25% of the experts from Qwen3-Coder-480B-A35B-Instruct using the REAP method. While maintaining performance close to the original model, it significantly reduces the parameter scale and memory requirements, making it particularly suitable for code generation and intelligent coding scenarios with limited resources.

Natural Language ProcessingTransformersEnglish

Qwen3-Coder-480B-A35B-Instruct is a large code generation model with 480 billion parameters, supporting 8.5-bit quantization and optimized based on the MLX framework. This model is specifically designed for code generation tasks and can run efficiently on devices with sufficient memory.

Natural Language ProcessingMlxEnglish

This project is the result of MXFP4_MOE quantization of the Qwen3-Coder-30B-A3B-Instruct model. It extends the context size from 256k to 1M, providing a more optimized model version for code generation and programming tasks, with the value of improving performance and saving resources.

MultimodalGguf

This is a quantized version based on Qwen3-Coder-REAP-25B-A3B, specifically optimized for Mac devices. It uses the Deckard (qx) formula for quantization, with 6-bit quantization for the embedding layer, heads, and selective attention paths, and 5-bit quantization for the rest, with a group size of 32. It achieves more efficient operation while maintaining a quality close to q8 quantization.

Natural Language ProcessingMlxEnglish

This is the MXFP4_MOE quantized version of the Qwen3-Coder-REAP-25B-A3B model, specifically designed for text generation tasks. This model is based on the 25B parameter Qwen3-Coder architecture, and the storage and inference efficiency are optimized through the MXFP4 quantization technology while maintaining good performance.

Natural Language ProcessingGguf

This is an MLX format version converted from the Qwen3-Coder-REAP-25B-A3B model, converted from the original model using the mlx-lm tool, specifically optimized for Apple Silicon chips, and supports efficient text generation tasks.

Natural Language ProcessingMlxEnglish

This model is a GGUF format conversion version of cerebras/Qwen3-Coder-REAP-25B-A3B, which uses the llama.cpp tool for format conversion and quantization processing. The original model is a large language model with 25B parameters, specifically optimized for code generation tasks.

Natural Language ProcessingTransformersEnglish

This is a quantized version of the Qwen3-Coder-REAP-25B-A3B model from Cerebras. It uses the imatrix technology of llama.cpp for quantization, which can reduce the model storage space and computational resource requirements while maintaining the model performance.

Natural Language ProcessingGguf

UIGENT-30B-Lora-200 is a large language model fine-tuned based on Qwen3-Coder-30B-A3B-Instruct. It is specifically optimized for text generation tasks and is particularly good at handling HTML-related content. It also has various text generation capabilities.

Natural Language ProcessingTransformers

This is a mixture-of-experts model based on Qwen3-Coder-30B-A3B-Instruct, with 54 billion parameters and a context length of 1 million. The model has powerful programming capabilities and general scenario processing capabilities through three-step merging and Brainstorm 40X optimization. It is especially integrated with a thinking module, which can perform in-depth reasoning before answering.

Natural Language ProcessingTransformersMultiple Languages

This is the GGUF quantized version of the Qwen3-Coder-30B-A3B-Instruct language model, specifically optimized for code generation and programming tasks. It supports multiple quantization levels to meet different hardware requirements.

Natural Language ProcessingGgufMultiple Languages

This is the GGUF quantized version of the Qwen/Qwen3-Coder-30B-A3B-Instruct language model, optimized for local inference and supporting frameworks such as llama.cpp, LM Studio, OpenWebUI, and GPT4All. This model is a code generation and programming assistant model with a parameter scale of 30B.

Natural Language ProcessingGgufMultiple Languages

This is a quantized version based on the Qwen3-Coder-30B model, a language model specifically optimized for code generation tasks. It provides various quantized files in GGUF format, significantly reducing the file size while maintaining model quality and improving inference speed.

Natural Language ProcessingGguf

Qwen3-Coder-480B-A35B-Instruct is a text generation model based on the MLX library, specifically optimized for code generation tasks. This model offers multiple quantization levels. Under 6.5-bit quantization, it can achieve a perplexity performance comparable to that of 8-bit quantization, significantly reducing resource requirements while maintaining high-quality output.

Natural Language ProcessingMlx

This is a 4-bit quantized version based on the Qwen3-Coder-30B-A3B-Instruct model, specifically optimized for the MLX framework. This model focuses on code generation and programming tasks, supports multiple programming languages, and has efficient inference performance.

Natural Language ProcessingMlx

This is the GGUF quantized version of the Qwen3-Coder-30B-A3B-Instruct model, provided by TensorBlock. This model is a large language model with 30 billion parameters, specifically optimized for code generation and programming tasks, supporting multiple programming languages and development scenarios.

Natural Language ProcessingTransformers

Qwen3-Coder-30B-A3B-Instruct is an efficient text generation model optimized specifically for coding tasks. It has excellent long context processing capabilities and tool call support, providing powerful coding assistance for developers.

Natural Language ProcessingSafetensors

This is a quantized version of the Qwen3-Coder-30B-A3B-Instruct model, converted to the gguf q4km format through the AutoRound algorithm. It can run efficiently on more devices while ensuring performance. This model is specifically designed for code generation tasks and supports multiple programming languages.

Natural Language ProcessingGguf