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  "path": "/t/successfully-running-gemma4-26b-on-prem-looking-to-discuss-deployment-struggles-stable-setups/176145#post_1",
  "publishedAt": "2026-05-21T10:31:52.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Hi everyone,\n\nI’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.\n\nDuring deployment, I ran into several issues including:\n\n  * CUDA driver mismatches\n\n  * PyTorch/CUDA compatibility problems\n\n  * vLLM engine initialization failures\n\n  * GemmaTokenizer compatibility errors\n\n  * Transformers version conflicts\n\n  * GPU initialization issues\n\n  * Docker vs native environment differences\n\n  * FlashAttention setup concerns\n\n\n\n\nAfter 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.\n\nWould love to discuss:\n\n  * Working CUDA + driver combinations\n\n  * Stable PyTorch/vLLM/Transformers versions\n\n  * Docker vs non-Docker deployment experiences\n\n  * Multi-GPU setups\n\n  * Quantized deployments\n\n  * Recommended inference settings\n\n  * Production stability observations\n\n\n\n\nIf anyone has successfully deployed Gemma4-26B reliably, I’d really appreciate hearing about your setup and lessons learned.\n\nThanks!",
  "title": "Successfully Running Gemma4-26B On-Prem? Looking to Discuss Deployment Struggles & Stable Setups"
}