Qwopus3.6 35B A3B Coder MTP Alternatives

Qwopus3.6-27B-Coder-MTP-GGUF is a 27 billion parameter multimodal model based on Qwen3, fine-tuned for coding, reasoning, and tool use. It supports image and text inputs and is distributed in GGUF format for local inference with llama.cpp. The model excels at programming tasks, chain-of-thought reasoning, and agentic workflows.

Qwopus3.6-27B-v2-MTP-GGUF is a GGUF-quantized multimodal model supporting image and text inputs with advanced multi-token prediction (MTP) capabilities for faster inference. It combines reasoning, coding, and vision abilities in a single model. It is compatible with llama.cpp-based tools and local inference runtimes.

A GGUF quantized variant of a 27-billion parameter model specialized for coding tasks (Qwopus3.6) that also includes multimodal (vision) capabilities. It uses NVFP4 quantization for efficient local inference. The model supports advanced prompting formats and is suitable for code generation and vision-language tasks on compatible hardware.

Qwopus-GLM-18B-Merged-GGUF is an open-source large language model distributed in GGUF format for local inference. It is designed for AI researchers and developers who require customizable, offline LLM capabilities.

This is a GGUF-formatted, NVFP4-quantized release of a 27-billion-parameter model (Qwopus 3.6 v2) that includes Multi-Token Prediction (MTP) capabilities. It is designed for efficient local execution via llama.cpp or compatible GGUF runtimes. The model targets users who need high-performance local LLMs on consumer hardware.

Qwen3-Coder-Next-GGUF is a collection of GGUF quantized files for the Qwen3-Coder-Next series of coding models, published by Unsloth. It enables efficient local inference of powerful coding LLMs on CPUs and GPUs using tools like llama.cpp. The models support advanced code generation, tool use, and follow a specialized chat template for programming tasks.

Qwopus3.6-27B-Coder-NVFP4 is a specialized, quantized version of a 27 billion parameter model optimized for coding tasks. It supports tool calling and follows an advanced chat template. The NVFP4 quantization allows it to run on a wide range of hardware while maintaining strong code generation capabilities.

Qwen3.6-27B-NVFP4-MTP-GGUF is a GGUF-quantized version of the Qwen 3.6 billion parameter language model, optimized for efficient local execution using tools like llama.cpp. It supports text generation and multimodal inputs, making it suitable for developers building offline AI applications. The model is hosted on Hugging Face and can be run via CLI or integrated into custom applications.

mudler/Qwen3.6-35B-A3B-APEX-MTP-GGUF provides GGUF quantized weights for a Qwen3.6 model incorporating A3B APEX MTP (Mixture-of-Experts or similar advanced technique) optimizations. It is designed for efficient local execution using tools such as llama.cpp. The model includes complex tokenizer configurations for multimodal or advanced prompting capabilities.

Qwen3.6-27B-MTP-GGUF is an open-source large language model distributed in GGUF format for efficient local inference. It enables developers to run advanced text generation tasks on their own hardware without relying on cloud services.

Qwen3-Coder-30B-A3B-Instruct-GGUF is an open-source large language model for code generation, distributed in GGUF format for local inference. It is designed for developers and researchers who require local, private AI code generation capabilities.

Qwen3-30B-A3B-GGUF provides GGUF quantized weights for the Qwen3 30B-A3B model, enabling efficient local execution with tools like llama.cpp. It supports advanced features including tool calling and follows a specific chat template for multi-turn conversations. The model is intended for developers who want to run powerful language models offline.

zlaabsi/Qwen3.6-27B-OTQ-GGUF provides GGUF quantized weights of the Qwen3.6 27B model, enabling efficient local inference with tools like llama.cpp. The model supports multimodal inputs and is suitable for developers who want to run powerful language and vision models on their own machines without cloud dependency.

This is a GGUF quantized version of the Qwen3.6-35B-A3B model using NVFP4 precision. It supports multimodal inputs including text and images. The model is optimized for local inference using tools that support the GGUF format.

This is a GGUF-quantized version of a Qwen3.5-9B model merged with DeepSeek capabilities, optimized for local inference. It includes support for tool calling and function execution. The model is designed for developers building local AI agents or applications that require structured output and external tool integration.