Local Deployment
Definition: Local deployment refers to setting up and running software or services on a personal computer or server within one’s own network rather than relying on cloud-based solutions. For large language models (LLMs), this involves downloading, installing, configuring, and running the model locally.
Key Considerations
- Resource Requirements: High computational power and storage space are essential.
- Privacy & Security: Data remains under personal control without needing to transmit it over potentially insecure networks.
- Customization: Ability to tailor model behavior and integration with other tools is enhanced.
Recent Dev
- RAM-Only Inference for Massive MoE Models: New techniques allow running extremely large Mixture of Experts (MoE) models, such as the 744B parameter GLM-5.2, on consumer-grade hardware with ~25GB RAM and no GPU. This demonstrates that quantization and efficient inference engines can bypass traditional VRAM bottlenecks for specific model architectures. See Colibri: Local GLM-5.2 (744B) RAM Inference with MoE, No GPU.