Qwen3.6 27B MTP Pi Tune Alternatives

Qwen3.6-27B-MTP-pi-tune-GGUF provides a GGUF-quantized version of a fine-tuned Qwen 3.6B parameter model. It supports text generation, multimodal inputs, and runs locally via libraries such as llama.cpp or Hugging Face Transformers. The model is intended for developers seeking efficient local inference of large language models with custom tuning.

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.

Qwen3.6-27B-NVFP4 is a community-quantized version of the Qwen3.6 27-billion parameter model using NVFP4 precision. It includes patches for improved coding-agent and tool-calling behavior. The model is hosted on Hugging Face and designed for efficient local or server-based inference on compatible NVIDIA hardware.

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.

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-NVFP4 is an FP4 quantized variant of the Qwen3.6-27B model. It supports both text and vision inputs including images and video through specialized tokens and templates. The model is designed for efficient local or hosted inference using the Transformers library and is available on the Hugging Face model hub.

This is an INT4 GPTQ-quantized version of the Qwen3.5-27B model from the Qwen team. It supports multimodal inputs including text, images, and video. The quantization enables more efficient inference while maintaining strong performance across various tasks.

This is a GGUF-formatted, quantized release of the Qwen3.5-122B model (with A10B active parameters, Mixture-of-Experts, and MTP). It supports multimodal inputs and is optimized for local inference using tools that consume the GGUF format. The model is distributed via the Unsloth organization on Hugging Face.

Qwen3.6-27B-FP8 is a community-quantized variant of Alibaba's Qwen3 model offered in FP8 precision for lower memory usage while retaining strong performance. It supports text and vision inputs and is compatible with the Hugging Face ecosystem for local or cloud deployment. It is intended for developers building efficient multimodal applications.

Qwen3.5-122B-A10B-NVFP4 is a highly quantized version of the large Qwen 3.5 model (122B parameters). It supports vision inputs alongside text and includes advanced tool-calling features. The model is distributed on Hugging Face for use in high-performance inference environments.

Qwen3.6-27B-MTP-GGUF is an open-source large language model for advanced text generation and AI research. It is distributed in GGUF format for efficient local inference and is suitable for developers and researchers in NLP.

Qwen3.6-27B-NVFP4 is an NVIDIA-optimized version of the Qwen3 27B model using NVFP4 quantization. It supports vision and video inputs in addition to text and includes a sophisticated tokenizer and chat template. The model is designed for efficient inference on NVIDIA GPUs while maintaining the strong performance of the original Qwen3 architecture.

This is a community-quantized version of the Qwen3.6-35B model using NVFP4 precision. It supports both text and vision inputs and is optimized for reduced memory usage and faster inference on compatible hardware. The model is intended for local deployment and experimentation.

A 4-bit AWQ quantized checkpoint of the Qwen3.5-35B-A3B Mixture-of-Experts model. It supports multimodal inputs including images and video and is optimized for local execution using tools compatible with the GGUF or AWQ format. The model is intended for developers wanting high-performance local AI 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.

Qwen3.5-2B-AWQ-4bit is a 4-bit AWQ quantized version of Alibaba's Qwen 3.5 2B model. It supports multimodal inputs including images and video in addition to text, along with tool calling capabilities. The model is distributed on Hugging Face for efficient local or edge deployment.

This is a community-quantized 8-bit version of Qwen3.6-35B (with A3B MoE architecture) prepared for the MLX framework on Apple devices. It enables high-performance local inference on Macs with reduced memory footprint while retaining strong reasoning capabilities. The model uses standard MLX conversion and loading patterns.

Qwen3-1.7B-FP8 is a quantized variant of Alibaba's Qwen3 series of large language models. It supports advanced features including tool calling and follows a chat template optimized for instruction following. The FP8 format enables faster inference with reduced memory requirements while maintaining strong performance.

This repository provides GGUF quantized files for the Qwen3.6-35B model using an A3B (likely MoE or distilled) architecture. It is optimized for local inference with tools such as LM Studio. The model includes advanced tool-calling capabilities and a sophisticated chat template for complex interactions.

Qwen3-30B-A3B-GPTQ-Int4 is a GPTQ 4-bit quantized variant of the Qwen3 30B-A3B model. It supports advanced capabilities such as tool calling and follows a detailed chat template for conversational use. The model is optimized for local or server-based inference using tools like llama.cpp or Hugging Face Text Generation Inference while maintaining strong performance.

This is a 4-bit AWQ quantized version of Alibaba's Qwen3.5-122B (A10B) model. Hosted on Hugging Face, it enables local inference of a powerful 122 billion parameter language model on consumer hardware. The model supports advanced features including tool calling and multimodal inputs.

GGUF quantized version of the Qwen3.5-9B model with Mixture-of-Transformers (MTP) and multimodal (vision) support. Optimized by Unsloth for fast local inference using llama.cpp or compatible runtimes. Supports text, image, and video understanding depending on the variant.

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.

A heavily quantized (4-bit AWQ) version of a Qwen 3.6 model with 35B+3B parameters and vision capabilities (VRAP). The 21.2GB model supports both text and image inputs. It is designed for local inference using GGUF-compatible tools or optimized runtimes.

Qwen3.6-35B-A3B-MLX-6bit is a 6-bit quantized version of the Qwen 3.6 model hosted by the lmstudio-community on Hugging Face. It belongs to the class of foundation models and is distributed as a repository containing model weights, tokenizer configuration, and a chat template that supports multimodal inputs. The repository includes a tokenizer definition with specific pad, end-of-text, and unknown tokens. Its chat template contains logic for processing mixed content, including separate handling for text strings and iterable content. The template detects image and video items, increments internal counters for each, prepends numbered labels such as "Picture 1:" when a flag is set, and inserts special vision markers. It explicitly prevents images or videos from appearing in system messages by raising an exception. The model is made available through the Hugging Face platform, which provides access to models, datasets, and related resources. No information is given on licensing, pricing, intended user roles, or specific hardware optimizations beyond what is encoded in the repository name and template.

This is a GGUF-quantized version of the Qwen3.6-35B-A3B model, optimized for efficient local inference using tools like llama.cpp. It supports multimodal inputs and is designed for developers who want to run powerful language models on standard hardware without relying on cloud APIs.

Qwen3.6-35B-A3B-AWQ-4bit is a quantized version of a large language model, designed for efficient inference on local hardware. It is suitable for developers and researchers who need high-performance language models with reduced resource requirements.

A 4 billion parameter version of the Qwen3 large language model in FP8 precision. It supports instruction following, tool calling, and general text generation. The model is hosted on Hugging Face and can be used locally or via inference providers.