You’ve got a powerful 24 GB GPU sitting on your Ubuntu 22.04 machine, you’ve containerized your Ollama + vLLM setup in Docker, and everything should be working beautifully. But instead, you’re staring at a dreaded “CUDA out of memory” error that makes absolutely no sense. Your GPU has more than enough memory, the container claims … Read more
It’s 2 AM. Your production AI service is down. Again. The logs scream “CUDA out of memory,” but your GPU has 24GB and your model is only 7B parameters. You upgraded vLLM to 0.3.0 last week, spun up your Docker containers on Ubuntu 22.04, and everything worked in development. Now your FastAPI server is crashing … Read more
Quick Overview Difficulty Level: Intermediate | Estimated Fix Time: 15-30 minutes | Required Knowledge: Docker, GPU drivers, CUDA basics This guide walks you through diagnosing and fixing CUDA version conflicts that cause memory allocation failures in containerized Ollama deployments. The Problem That Ate My Friday Night You’ve deployed your VPS with GPU support, spun up … Read more
You’ve upgraded vLLM to 0.5, and now your Ollama setup on Ubuntu 22.04 is crashing hard. The error message stares back at you: “CUDA out of memory.” Your Docker container was running smoothly yesterday. Today? It’s a memory leak nightmare. You’re not alone—this is a known issue affecting developers deploying large language models (LLMs) in … Read more
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
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
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
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
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
You’ve got Ollama installed on your Ubuntu 22.04 machine. You pull down a fresh language model. You run it. And then—nothing. The terminal freezes. Your system grinds to a halt. Or worse, you get a cryptic “out of memory” error and Ollama crashes hard. If you’ve been staring at this problem for the last hour … Read more