Native support for 23 languages. The single best open multilingual foundation model available for researchers building localized or translation-heavy pipelines.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 22GB VRAM Recommended
Origins & History
The Aya Expanse 32B model by CohereForAI is a 32B dense parameter architecture optimized for chat tasks. It requires approximately 20GB of VRAM to comfortably run locally using a Q4_K_M quantization. Extending the context window up to 131,072 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
Pros
Full privacy and offline inference capabilities
Highly capable 32B dense parameter structure
Supports impressive 131,072 token context window
Cons
Requires 20GB+ VRAM minimum
Local inference speed depends entirely on memory bandwidth (GB/s)
Architect's Runtime Strategy
For running Aya Expanse 32B 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.
Common Questions
What hardware do I need to run Aya Expanse 32B?
You will need a GPU with at least 22GB of VRAM to run the Q4_K_M quantized version smoothly with a moderate context window.
How do I install Aya Expanse 32B locally?
The simplest method is utilizing Ollama by executing 'ollama run aya-expanse:32b' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.