Ultra-compact sentence embedding model. Perfect for semantic search and RAG pipelines on any hardware.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 3GB VRAM Recommended
The all-MiniLM-L6 model by Sentence Transformers is a 22M parameter architecture optimized for embedding tasks. It requires approximately 0.1GB of VRAM to comfortably run locally using a FP32 quantization. Extending the context window up to 512 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
For running all-MiniLM-L6 at maximum tokens-per-second, we recommend using LM Studio or Ollama with a GGUF quantization (Q4_K_M or Q6_K). If you are multi-GPU, use vLLM to distribute the layers across your VRAM pool for optimal throughput.
You will need a GPU with at least 3GB of VRAM to run the FP32 quantized version smoothly with a moderate context window.
The simplest method is utilizing Ollama by executing 'ollama run all-minilm' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.