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  2. Keigo Slm Qwen3 1.7b/
  3. Alternatives

Keigo Slm Qwen3 1.7b Alternatives

keigo-slm-qwen3-1.7b-v2 is an open-source language model for text generation and inference, distributed via Hugging Face. Below are 18 foundation models & chat apps with similar functionality to Keigo Slm Qwen3 1.7b, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.

  • Keigo Slm Qwen3 1.7b
    huggingface.co

    keigo-slm-qwen3-1.7b is an open-source large language model checkpoint hosted on Hugging Face, designed for text generation and conversational AI tasks. It allows developers and researchers to run, fine-tune, and experiment with the model locally or in their own infrastructure. The model is suitable for a variety of natural language processing applications.

  • Qwen 3b Brain
    huggingface.co

    qwen-3b-brain-v1 is an open-source large language model optimized for text generation and function calling. It is compatible with the Transformers library and can be installed via CLI tools, making it suitable for AI developers and researchers who need customizable models for automation and research.

  • Qwen3.5 9B
    huggingface.co

    Qwen3.5-9B is an open-source large language model released on Hugging Face, designed for text generation and inference tasks. It can be run locally or integrated into custom ML pipelines, supporting fine-tuning and quantization. Ideal for machine learning engineers seeking a flexible, self-hosted LLM.

  • Qwen3.6 35b A3b Arfp4 Ebssmix G64r256
    huggingface.co

    qwen3.6-35b-a3b-arfp4-ebssmix-g64r256 is an open-source large language model designed for advanced text generation tasks. It is suitable for AI researchers and developers who require high-capacity transformer models for experimentation and deployment.

  • Qwen3 8b Human Sft
    huggingface.co

    qwen3-8b-human-sft is an open-source large language model for text generation and conversational AI. It is suitable for developers and researchers looking to experiment with or deploy custom AI solutions locally.

  • Qwen3.5 27B MLX 4.5bit
    huggingface.co

    Qwen3.5-27B-MLX-4.5bit is an open-source, quantized large language model designed for efficient local text generation using the MLX framework. It supports local inference and is suitable for developers and researchers seeking to run LLMs on their own hardware.

  • Qwen3.5 4B EU Q4 K M
    huggingface.co

    Qwen3.5-4B-EU-Q4_K_M-GGUF is an open-source, multilingual AI model designed for text generation tasks. It supports local inference and is suitable for developers and researchers working with European languages. Distributed under the Apache 2.0 license.

  • Qwen3.6 35B A3B Vram13
    huggingface.co

    Qwen3.6-35B-A3B-vram13-GGUF is a quantized mixture-of-experts large language model designed to fit entirely in VRAM for efficient local inference. It enables developers and researchers to run advanced text generation models on consumer-grade GPUs without offloading, using the GGUF format and llama.cpp compatibility.

  • Qwen3 0.6b Itbench K8s Grpo
    huggingface.co

    qwen3-0.6b-itbench-k8s-grpo is an open-source language model for text generation, available on Hugging Face. It is intended for developers and researchers working on NLP tasks and supports local deployment via pip.

  • Qwen2.5 7b Final Merged
    huggingface.co

    qwen2.5-7b-final-merged 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.

  • Qwen3.6 27B Text NVFP4 MTP
    huggingface.co

    Qwen3.6-27B-Text-NVFP4-MTP is an open-source large language model designed for text and code generation, with features supporting coding agents and tool-calling. It can be run locally and is suitable for AI researchers and developers seeking customizable LLMs.

  • Qwen2.5 7b Stage1 Merged
    huggingface.co

    qwen2.5-7b-stage1-merged is an open-source language model based on Qwen 2.5, designed for text generation and conversational AI. It is suitable for developers and researchers to run locally or integrate into custom applications, supporting prompt engineering and experimentation.

  • Qwen3 30B A3B
    huggingface.co

    Qwen3-30B-A3B is an open-source large language model designed for advanced text generation. Distributed under the Apache 2.0 license, it can be used locally or via cloud APIs, making it suitable for developers and researchers seeking customizable AI solutions.

  • Srishtik/Qwen3-0.6B-linear-3-adapters-merged-2
    huggingface.co

    Srishtik/Qwen3-0.6B-linear-3-adapters-merged-2 is an open-source language model with linear adapters for text generation, available on Hugging Face. It is intended for ML engineers and researchers working on advanced NLP applications.

  • Qwen3 1.7B
    huggingface.co

    Qwen3-1.7B-GGUF is an open-source checkpoint of the Qwen3 language model in GGUF format, designed for local inference and text generation. It is suitable for developers and researchers who want to integrate or experiment with large language models in their own environments.

  • Qwen2.5 1.5b Eagle Cot Seed42 Es Val0.15 Pat3
    huggingface.co

    qwen2.5-1.5b-eagle-cot-seed42-es-val0.15-pat3 is an open-source language model hosted on Hugging Face, designed for text generation and research purposes. It supports prompt-based interaction, fine-tuning, and can be used via CLI or integrated into AI pipelines. Ideal for AI researchers and developers seeking customizable LLMs.

  • Qwen2.5 7b Numbers Xi S2
    huggingface.co

    qwen2.5-7b-numbers-xi-s2 is an open-source language model based on Qwen 2.5, designed for text generation and conversational AI. It is suitable for developers and researchers to run locally or integrate into custom applications, supporting prompt engineering and experimentation.

  • Qwen3.5 9B IQ4 NL
    huggingface.co

    Qwen3.5-9B-IQ4_NL-GGUF is an open-source checkpoint of the Qwen 3.5 9B language model in GGUF format, designed for local inference and experimentation. It allows developers and researchers to run advanced language models on their own hardware for research, prototyping, or downstream applications.