Successfully Running Gemma4-26B On-Prem? Looking to Discuss Deployment Struggles & Stable Setups

Hi everyone, I’ve been working on deploying Gemma4-26B on-premise at a server level using vLLM, and I wanted to connect with others who have successfully set it up or faced similar challenges. During deployment, I ran into several issues including: * CUDA driver mismatches * PyTorch/CUDA compatibility problems * vLLM engine initialization failures * GemmaTokenizer compatibility errors * Transformers version conflicts * GPU initialization issues * Docker vs native environment differences * FlashAttention setup concerns After multiple debugging attempts and environment changes, I’m trying to understand what deployment stacks are currently the most stable for Gemma4-26B in production/on-prem environments. Would love to discuss: * Working CUDA + driver combinations * Stable PyTorch/vLLM/Transformers versions * Docker vs non-Docker deployment experiences * Multi-GPU setups * Quantized deployments * Recommended inference settings * Production stability observations If anyone has successfully deployed Gemma4-26B reliably, I’d really appreciate hearing about your setup and lessons learned. Thanks!