vllm

vLLM Docker container keeps crashing on Ubuntu 22.04 with “CUDA out of memory” – how I fixed the GPU driver/version mismatch and prevented the out‑of‑memory timeout.

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You’ve deployed a vLLM container to your Ubuntu 22.04 VPS to run large language model inference, everything looks good in the Docker logs for about thirty seconds, and then—crash. “CUDA out of memory” appears, your container exits with code 139 or 137, and your inference pipeline collapses. You’ve checked your GPU memory with nvidia-smi, and … Read more

vLLM Docker container keeps crashing with “CUDA out of memory” on Ubuntu 22.04 (RTX 4090) – step‑by‑step fix for the GPU memory leak and version mismatch issue.

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You’ve been running vLLM in Docker for LLM inference, everything seemed fine in development, and then BAM—your container crashes with “CUDA out of memory” after a few minutes. Your RTX 4090 has 24GB of VRAM, but it’s behaving like you’re running on a laptop with 2GB. This is one of the most frustrating debugging sessions … Read more

Fix “CUDA out of memory” error when launching Ollama Llama 2 via vLLM in a Docker container on Ubuntu 22.04 VPS with 8 GB GPU – step‑by‑step debugging guide

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You’ve got Ollama and vLLM set up on your Ubuntu VPS. You spin up the Docker container, everything looks ready, and then it hits you: CUDA out of memory. Your 8 GB GPU isn’t even close to being maxed out, but the error won’t budge. If this sounds familiar, you’re not alone—and the solution is … Read more

How I Fixed Ollama Docker crashing on Ubuntu 22.04 WSL2 with “CUDA out of memory” – resolving CUDA 12.1 vs vLLM version mismatch and GPU driver errors

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When “CUDA out of memory” means you’re stuck If you’ve tried to spin up Ollama inside Docker on a WSL2 Ubuntu 22.04 VM and the container dies with a cryptic CUDA out of memory error, you know the feeling: you’re ready to dive into AI tools, but a tiny driver mismatch yanks the rug from under … Read more

Docker Compose “vllm: failed to start” on Ubuntu 22.04 – fixing CUDA 12 vs torch 2.2 “CUDA out of memory” error in a GPU‑enabled FastAPI LLM service.

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You’ve containerized your large language model service with vllm, you’ve got a beefy GPU, but Docker keeps throwing cryptic CUDA memory errors. Your FastAPI LLM service won’t even start. Let’s fix this—and fast. Quick Reference Use Case: GPU-accelerated LLM inference with Docker on Ubuntu 22.04 Difficulty Level: Intermediate Estimated Fix Time: 15–30 minutes Primary Stack: … Read more