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  2. Qwopus GLM 18B Merged/
  3. Alternatives

Qwopus GLM 18B Merged Alternatives

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. Below are 12 coding ai & assistants apps with similar functionality to Qwopus GLM 18B Merged, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.

  • Qwen3.5 27B
    huggingface.co

    Qwen3.5-27B-GGUF is an open-source large language model released in GGUF format for local inference and experimentation. It is suitable for AI researchers and developers who require access to model weights and the ability to run models on their own hardware.

  • Qwen3.6 27B
    huggingface.co

    Qwen3.6-27B-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 a powerful language model that can be run on local hardware for experimentation and development.

  • Qwen3.5 35B A3B
    huggingface.co

    Qwen3.5-35B-A3B-GGUF is an open-source large language model designed for local inference and research. It enables developers and researchers to run text generation tasks efficiently on their own hardware with open weights.

  • Qwen3.5 35B A3B
    huggingface.co

    Qwen3.5-35B-A3B-GGUF is an open-source large language model distributed by Unsloth on Hugging Face. It supports local inference, multiple quantizations, and is designed for AI researchers and developers seeking to run LLMs on their own hardware.

  • Qwen3.6 35B A3B
    huggingface.co

    Qwen3.6-35B-A3B-GGUF is an open-source, quantized large language model distributed in GGUF format for local inference and research. It enables developers and researchers to run advanced language models on their own hardware, supporting experimentation and customization. The model is freely available for use and modification.

  • Qwen3.6 35B A3B
    huggingface.co

    Qwen3.6-35B-A3B-GGUF is a large language model checkpoint in GGUF format, designed for local inference and CLI-based workflows. It enables developers and researchers to run advanced language models on their own hardware for experimentation and application development.

  • Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled
    huggingface.co

    Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF is an open-source AI model designed for advanced reasoning tasks. Distributed in GGUF format, it allows developers and researchers to run large language models locally via CLI tools, supporting privacy and customization.

  • Qwen3.6 27B
    huggingface.co

    Qwen3.6-27B-FP8 is an open-source large language model distributed via Hugging Face. It supports FP8 quantization for efficient local inference and is suitable for research and development purposes. The model is accessible to AI researchers and developers.

  • Bubip Qwen3 14b
    huggingface.co

    bubip-qwen3-14b-GGUF is an open-source large language model for text generation and inference. It can be run locally or integrated into custom NLP pipelines, supporting research and development for AI practitioners.

  • Qwen3.5 0.8B
    huggingface.co

    Qwen3.5-0.8B-GGUF is an open-source foundation language model distributed in GGUF format for local inference. It enables developers and researchers to run advanced text generation tasks on their own hardware without relying on cloud APIs.

  • Qwen3 Coder 30B A3B Instruct
    huggingface.co

    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.

  • Qwen35B Agent R2
    huggingface.co

    Qwen35B-Agent-R2-GGUF is an open-source checkpoint of the Qwen 35B language model, designed for advanced text generation and agent-based AI tasks. It supports local inference and customization, making it suitable for AI researchers and developers integrating large models into their workflows.