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--- |
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library_name: transformers |
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license: apache-2.0 |
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license_link: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct/blob/main/LICENSE |
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pipeline_tag: text-generation |
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base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct |
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tags: |
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- llama-cpp |
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- text-generation-inference |
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language: |
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- en |
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--- |
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# **Qwen3-Coder-30B-A3B-Instruct-GGUF** |
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> Qwen3-Coder-30B-A3B-Instruct is a state-of-the-art large language model from the Qwen series, specifically optimized for advanced agentic coding, browser-based automation, and foundational programming tasks. Featuring 30.5 billion total parameters with 3.3 billion activated in a Mixture-of-Experts (MoE) architecture, it delivers strong performance and efficiency for complex code and tool-use scenarios. Its standout long-context capability natively processes up to 262,144 tokens—expandable to 1 million with Yarn—making it ideal for repository-scale code understanding and generation. |
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> The model supports agentic coding with advanced function-call handling, and is compatible with popular local inference platforms like Ollama, LMStudio, and llama.cpp. Designed for both pretraining and post-training stages, Qwen3-Coder-30B-A3B-Instruct runs exclusively in non-thinking mode, ensuring fast, high-quality outputs for coding and automation workflows without requiring explicit configuration for thinking blocks |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo prithivMLmods/Qwen3-Coder-30B-A3B-Instruct-GGUF --hf-file qwen3-coder-30b-a3b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo prithivMLmods/Qwen3-Coder-30B-A3B-Instruct-GGUF --hf-file qwen3-coder-30b-a3b-instruct-q4_k_m.gguf -c 2048 |
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``` |
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo prithivMLmods/Qwen3-Coder-30B-A3B-Instruct-GGUF --hf-file qwen3-coder-30b-a3b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo prithivMLmods/Qwen3-Coder-30B-A3B-Instruct-GGUF --hf-file qwen3-coder-30b-a3b-instruct-q4_k_m.gguf -c 2048 |
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``` |
