qwen3-8b-instruct-indo-sft is an open-source, instruction-tuned language model checkpoint supporting Indonesian and English. Below are 21 foundation models & chat apps with similar functionality to Qwen3 8b Instruct Indo Sft, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
Qwen2.5-3B-Instruct is an open-source, instruction-tuned large language model designed for advanced text generation and conversational AI applications. It is suitable for AI researchers and developers seeking a customizable LLM for research or integration into applications. The model supports API and CLI deployment.
Qwen2.5-3B-Instruct is an open-source, fine-tuned large language model optimized for instruction following and text generation. It is suitable for NLP developers and researchers integrating LLMs into their workflows.
Qwen2.5-7B-Instruct is an open-source large language model developed by Alibaba Cloud, designed for instruction following and general AI tasks. It can be self-hosted or accessed via API, and is suitable for developers and researchers building AI applications or conducting experiments.
Qwen3-7B-Instruct-Q4_K_M-GGUF is a quantized version of the Qwen3-7B-Instruct large language model, designed for efficient local inference via CLI tools. It is open-source and suitable for developers and researchers needing instruction-following LLMs on local hardware.
Qwen2.5-14B-Instruct-AWQ is an open-source large language model designed for instruction following and conversational tasks. It provides downloadable weights and supports local inference, making it suitable for researchers and developers seeking customizable LLM solutions.
Qwen3-Coder-30B-A3B-Instruct-FP8 is an open-source, quantized large language model for code generation and instruction following. It supports local deployment via CLI or Docker, making it suitable for developers and researchers in AI and automation.
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.
qwen-3b-legal-indo-rag is an open-source AI language model tailored for legal and Indonesian retrieval-augmented generation tasks. It is designed for developers and researchers working in legal tech or multilingual AI, supporting pip and docker installation for flexible deployment.
Qwen3.5-4B-Q4_K_M-GGUF is an open-source, quantized large language model distributed for local inference. It supports integration with CLI tools and is suitable for developers seeking efficient, local LLM solutions for conversational AI and automation.
Qwen3-8B-school-of-reward-hacks is an open-source, instruction-tuned large language model designed for local inference and research. It supports text generation and is distributed for use with CLI and Docker, targeting AI researchers and developers interested in reward modeling and instruction following.
Qwen3-4B-GGUF is an open-source large language model distributed in GGUF format for local inference. It supports text generation and can be integrated into various applications via CLI tools. Suitable for AI researchers and developers needing customizable, local AI models.
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.
qwen2.5-7b-numbers-xi-s4 is a variant of the Qwen2.5-7B language model, fine-tuned for enhanced instruction following and conversational tasks. It is distributed as open source for local inference and research applications.
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.
Qwen3-Embedding-8B-Q8_0-GGUF is an open-source text embedding model distributed in GGUF format for efficient local inference. It enables developers and researchers to generate high-quality embeddings for various NLP tasks without depending on cloud APIs. The model is suitable for machine learning engineers seeking open, self-hosted solutions.
Qwen2.5-VL-72B-Instruct is an open-source, large-scale foundation model capable of understanding and generating text, images, and videos. It is designed for AI researchers and developers building advanced multimodal applications and can be deployed locally or via API.
Qwen3-Coder-30B-A3B-Instruct-GGUF is an open-source AI model for code generation and completion, available on Hugging Face. It can be installed via CLI tools and is designed for developers who want to run large language models for programming tasks locally.
Qwen2.5-Coder-1.5B-Instruct-Q3_K_S-GGUF is an open-source AI model checkpoint for code generation and instruction following. It is designed for local inference and experimentation, supporting integration into custom developer workflows. Distributed under the Apache 2.0 license.
qwen3-4b-pakistani-banking is an open-source language model fine-tuned for the Pakistani banking sector. It enables developers to build and experiment with banking-specific NLP applications, supporting deployment via CLI or API.
Qwen3.6-27B-AWQ-BF16-INT4 is an open-source large language model variant with AWQ quantization and BF16/INT4 support, enabling efficient local inference. Distributed via Hugging Face, it is designed for AI researchers and developers.
Qwen3.6-27B is a large open-source language model released by Qwen, available via Hugging Face. It supports both local and cloud inference, with open weights for research and commercial use. Developers can install it using pip or Docker and integrate it into their AI workflows.
