Best practices for deploying quantized open-weights models and proprietary LLMs with sub-200ms streaming latency.
1. Managed vs. Self-Hosted vLLM Inference
Varixen supports both managed API endpoints (OpenAI, Anthropic) and dedicated GPU cluster inference powered by vLLM and TensorRT-LLM on NVIDIA H100/A100 instances.
2. Model Quantization (AWQ / GPTQ)
Quantizing 70B parameter models to 4-bit AWQ formats reduces GPU memory requirements by 70% while preserving 99.2% of full-precision reasoning benchmark scores.