Ollama gpu linux reddit I see that the model's size is fairly evenly split amongst the 3 GPU, and the GPU processor utilization rate seems to go up at different GPUs @ different times. I see the same with a AMD GPU on Linux. As I have only 4GB of VRAM, I am thinking of running whisper in GPU and ollama in CPU. Alternatively, is there any way to force ollama to not use VRAM? Ollama + deepseek-v2:236b runs! AMD R9 5950x + 128GB Ram (DDR4@3200) + 3090TI 23GB Usable Vram + 256GB Dedicated Page file on NVME Drive. From using "nvidia-smi" on the terminal repeatedly. Might the gpu to be too new atm? Aug 25, 2024 · Setting environment variables on Linux. OLLAMA_MODELS The path to the models directory (default is "~/. cpp work well for me with a Radeon GPU on Linux. All CPU cores are going full, but memory is reserved on the GPU with 0% GPU usage. Docker wont find the GPU when trying to use openwebui with gpu integration. I was happy enough with AMD to upgrade from a 6650 to a 6800 (non-xt) for the more ram and performance boost. For each environment variable, add a line Environment under section [Service]: Aug 2, 2023 · I've tried with both ollama run codellama and ollama run llama2-uncensored. 5GB while idling. Unfortunately, the response time is very slow even for lightweight models like tinyllama. If Ollama is run as a systemd service, environment variables should be set using systemctl: Edit the systemd service by calling sudo systemctl edit ollama. So the plan is spin up a Proxmox deployment (bare metal) and then spin up a deployment of Ollama running in a VM with GPU pass-through. When I start the Ollama server and run my script, I can see with nvidia-smi that the Ollama server is loaded into GPU memory. Apr 8, 2025 · Have anyone got Ollama to use the AMD 9070XT gpu in Linux yet? I"m running Ollama in docker with the stuff I found I need but it still only using CPU. Just not sure how to get ollama to interface with it. However, shouldn’t I be able to see that Ollama is actively using the GPU with the nvtop command? It seems that during text generation, Ollama is only using the CPU, as I need to run ollama and whisper simultaneously. 1. Maybe the package you're using doesn't have cuda enabled, even if you have cuda installed. . I have 3x 1070. We would like to show you a description here but the site won’t allow us. I've already checked the GitHub and people are suggesting to make sure the GPU actually is available. I've just installed Ollama (via snap packaging) in my system and chatted with it a bit. / substring. service. Good catch 👍 (leefde) I didn't saw this one before, so i definitely will do some deep diving into that board and the corresponding CPU's. as far as I can tell, the advantage of multiple gpu is to increase your VRAM capacity to load larger models. CVE-2024-37032 View Ollama before 0. Linux isn't that much more CPU-friendly, but its WAY more memory-friendly. I'm using NixOS, not that it should matter. It seems that Ollama is in CPU-only mode and completely ignoring the GPU. This will open an editor. Ollama and llama. Feb 12, 2025 · Unlike NVIDIA GPUs, which have well-established CUDA support, AMD relies on ROCm (Radeon Open Compute) to enable GPU acceleration. Sep 17, 2024 · I have a question regarding Ollama and GPU usage. (Supermicro H12SSL-I Server Motherboard) We would like to show you a description here but the site won’t allow us. Gets about 1/2 (not 1 or 2, half a word) word every few seconds. Operating System: Debian GNU/Linux 12 (bookworm) Product Name: HP Compaq dc5850 SFF PC CPU: AMD Phenom(tm) II X4 B97 RAM: 8GB DDR2 Additonally, when I run text-generation-web-ui, that seems to use my GPU, but when running 7b models I run into issues, but regardless, it at least shows my gpu is working correctly in some way. In theory, you can run larger models in linux without the swap-space killing the generation speed. In this guide, we’ll walk you through the process of configuring Ollama to take advantage of your AMD GPU, ensuring optimal performance for running AI models fast and efficiently. 34 does not validate the format of the digest (sha256 with 64 hex digits) when getting the model path, and thus mishandles the TestGetBlobsPath test cases such as fewer than 64 hex digits, more than 64 hex digits, or an initial . If you use anything other than a few models of card you have to set an environment variable to force rocm to work, but it does work, but that’s trivial to set. ollama/models") OLLAMA_KEEP_ALIVE The duration that models stay loaded in memory (default is "5m") OLLAMA_DEBUG Set to 1 to enable additional debug logging Just set OLLAMA_ORIGINS to a drive:directory like: SET OLLAMA_MODELS=E:\Projects\ollama. The catch is that windows 11 uses about 4GB of memory just idling while linux uses more like ~0. Check if there's a ollama-cu Are you running models too big for your GPU? I’m also running an Ubuntu machine - testing the same thing last night. Additional Info System Specifications. Command-r runs but won’t touch the GPUs (2x 3090s) because of model size (I believe). Hi :) Ollama was using the GPU when i initially set it up (this was quite a few months ago), but recently i noticed the inference speed was low so I started to troubleshoot. The tokens are produced at roughly the same rate as before. How do I force ollama to stop using GPU and only use CPU. Don't know Debian, but in arch, there are two packages, "ollama" which only runs cpu, and "ollama-cuda". trldqj stq rka rdjhtee pnxv rbqquru qccxn yjqqljls sbjlaff bqpj