move ai notes from framework_desktop to software_ai_stack
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# Self Hosted AI Stack
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- [Self Hosted AI Stack](#self-hosted-ai-stack)
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- [Notes](#notes)
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- [Podman Volume Locations](#podman-volume-locations)
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- [Setup](#setup)
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- [Create the AI user](#create-the-ai-user)
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- [Helper aliases](#helper-aliases)
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- [Create the models dir](#create-the-models-dir)
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- [Install the Hugging Face CLI](#install-the-hugging-face-cli)
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- [Samba Model Storage](#samba-model-storage)
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- [Download models](#download-models)
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- [Text models](#text-models)
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- [GPT-OSS](#gpt-oss)
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- [Mistral](#mistral)
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- [Qwen](#qwen)
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- [GLM](#glm)
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- [Gemma](#gemma)
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- [Dolphin](#dolphin)
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- [Image models](#image-models)
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- [Z-Image](#z-image)
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- [Flux](#flux)
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- [Embedding Models](#embedding-models)
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- [Nomic](#nomic)
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- [llama.cpp](#llamacpp)
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- [stable-diffusion.cpp](#stable-diffusioncpp)
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- [open-webui](#open-webui)
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- [Install Services with Quadlets](#install-services-with-quadlets)
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- [Internal and External Pods](#internal-and-external-pods)
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- [Llama CPP Server](#llama-cpp-server)
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- [Stable Diffusion CPP](#stable-diffusion-cpp)
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- [Open Webui](#open-webui-1)
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- [Install the update script](#install-the-update-script)
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- [Install Guest Open Webui with Start/Stop Services](#install-guest-open-webui-with-startstop-services)
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- [Benchmark Results](#benchmark-results)
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## Notes
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### Podman Volume Locations
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`~/.local/share/containers/storage/volumes/`
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## Setup
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### Create the AI user
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```bash
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# Create your local ai user. This will be the user you launch podman processes from.
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useradd -m ai
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loginctl enable-linger ai
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su -l ai
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mkdir -p /home/ai/.config/containers/systemd/
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mkdir -p /home/ai/.ssh
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```
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Models are big. You'll want some tools to help find large files quickly when space runs out.
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### Helper aliases
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Add these to your .bashrc:
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```bash
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# Calculate all folder sizes in current dir
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alias {dudir,dud}='du -h --max-depth 1 | sort -h'
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# Calculate all file sizes in current dir
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alias {dufile,duf}='ls -lhSr'
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# Restart llama-server / follow logs
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alias llama-reload="systemctl --user daemon-reload && systemctl --user restart llama-server.service"
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alias llama-logs="journalctl --user -fu llama-server"
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# Restart stable diffusion gen and edit server / follow logs
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alias sd-gen-reload='systemctl --user daemon-reload && systemctl --user restart stable-diffusion-gen-server'
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alias sd-gen-logs='journalctl --user -xeu stable-diffusion-gen-server'
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alias sd-edit-reload='systemctl --user daemon-reload && systemctl --user restart stable-diffusion-edit-server'
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alias sd-edit-logs='journalctl --user -xeu stable-diffusion-edit-server'
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```
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### Create the models dir
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```bash
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mkdir -p /home/ai/models/{text,image,video,embedding,tts,stt}
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```
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### Install the Hugging Face CLI
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<https://huggingface.co/docs/huggingface_hub/en/guides/cli#getting-started>
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```bash
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# Install
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curl -LsSf https://hf.co/cli/install.sh | bash
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# Login
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hf auth login
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```
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### Samba Model Storage
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I recommend adding network storage for keeping models offloaded. This mounts a samba share at `/srv/models`.
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```bash
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dnf install -y cifs-utils
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# Add this to /etc/fstab
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//driveripper.reeselink.com/smb_models /srv/models cifs _netdev,nofail,uid=1001,gid=1001,credentials=/etc/samba/credentials 0 0
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# Then mount
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systemctl daemon-reload
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mount -a --mkdir
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```
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Here are some sync commands that I use to keep the samba share in sync with the home directory:
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```bash
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# Sync models from home dir to the samba share
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rsync -av --progress /home/ai/models/ /srv/models/
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```
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### Download models
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In general I try to run 8 bit quantized minimum.
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#### Text models
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<https://huggingface.co/ggml-org/collections>
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##### GPT-OSS
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<https://unsloth.ai/docs/models/gpt-oss-how-to-run-and-fine-tune#recommended-settings>
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```bash
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# gpt-oss-120b
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mkdir gpt-oss-120b && cd gpt-oss-120b
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hf download --local-dir . ggml-org/gpt-oss-120b-GGUF
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# gpt-oss-20b
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mkdir gpt-oss-20b && cd gpt-oss-20b
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hf download --local-dir . ggml-org/gpt-oss-20b-GGUF
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```
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##### Mistral
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```bash
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# devstral-small-2-24b
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mkdir devstral-small-2-24b && cd devstral-small-2-24b
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hf download --local-dir . ggml-org/Devstral-Small-2-24B-Instruct-2512-GGUF Devstral-Small-2-24B-Instruct-2512-Q8_0.gguf
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# ministral-3-14b
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mkdir ministral-3-14b && cd ministral-3-14b
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hf download --local-dir . ggml-org/Ministral-3-14B-Reasoning-2512-GGUF
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# ministral-3-3b-instruct
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mkdir ministral-3-3b-instruct && cd ministral-3-3b-instruct
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hf download --local-dir . ggml-org/Ministral-3-3B-Instruct-2512-GGUF
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```
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##### Qwen
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```bash
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# qwen3-30b-a3b-thinking
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mkdir qwen3-30b-a3b-thinking && cd qwen3-30b-a3b-thinking
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hf download --local-dir . ggml-org/Qwen3-30B-A3B-Thinking-2507-Q8_0-GGUF
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# qwen3-30b-a3b-instruct
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mkdir qwen3-30b-a3b-instruct && cd qwen3-30b-a3b-instruct
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hf download --local-dir . ggml-org/Qwen3-30B-A3B-Instruct-2507-Q8_0-GGUF
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# qwen3-vl-30b-a3b-thinking
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mkdir qwen3-vl-30b-a3b-thinking && cd qwen3-vl-30b-a3b-thinking
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hf download --local-dir . Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF Qwen3VL-30B-A3B-Thinking-Q8_0.gguf
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hf download --local-dir . Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF mmproj-Qwen3VL-30B-A3B-Thinking-F16.gguf
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# qwen3-vl-30b-a3b-instruct
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mkdir qwen3-vl-30b-a3b-instruct && cd qwen3-vl-30b-a3b-instruct
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hf download --local-dir . Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF Qwen3VL-30B-A3B-Instruct-Q8_0.gguf
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hf download --local-dir . Qwen/Qwen3-VL-30B-A3B-Instruct-GGUF mmproj-Qwen3VL-30B-A3B-Instruct-F16.gguf
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# qwen3-coder-30b-a3b-instruct
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mkdir qwen3-coder-30b-a3b-instruct && cd qwen3-coder-30b-a3b-instruct
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hf download --local-dir . ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
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# qwen3-coder-next
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mkdir qwen3-coder-next && cd qwen3-coder-next
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hf download --local-dir . unsloth/Qwen3-Coder-Next-GGUF --include "Q8_0/*.gguf"
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```
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##### GLM
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```bash
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# glm-4.7-flash-30b
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mkdir glm-4.7-flash-30b && cd glm-4.7-flash-30b
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hf download --local-dir . unsloth/GLM-4.7-Flash-GGUF GLM-4.7-Flash-Q8_0.gguf
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```
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##### Gemma
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```bash
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# Note "it" vs "pt" suffixes. "it" is instruction following, "pt" is the base model (not as good for out-of-the-box use)
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# gemma-3-27b-it
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mkdir gemma-3-27b-it && cd gemma-3-27b-it
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hf download --local-dir . unsloth/gemma-3-27b-it-GGUF gemma-3-27b-it-Q8_0.gguf
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hf download --local-dir . unsloth/gemma-3-27b-it-GGUF mmproj-F16.gguf
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```
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##### Dolphin
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```bash
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# dolphin-mistral-24b-venice
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mkdir dolphin-mistral-24b-venice && cd dolphin-mistral-24b-venice
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cd dolphin-mistral-24b-venice
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hf download --local-dir . bartowski/cognitivecomputations_Dolphin-Mistral-24B-Venice-Edition-GGUF cognitivecomputations_Dolphin-Mistral-24B-Venice-Edition-Q8_0.gguf
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```
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#### Image models
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##### Z-Image
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```bash
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# z-turbo
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# Fastest image generation in 8 steps. Great a text and prompt following.
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# Lacks variety.
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mkdir /home/ai/models/image/z-turbo && cd /home/ai/models/image/z-turbo
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hf download --local-dir . leejet/Z-Image-Turbo-GGUF z_image_turbo-Q8_0.gguf
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hf download --local-dir . black-forest-labs/FLUX.1-schnell ae.safetensors
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hf download --local-dir . unsloth/Qwen3-4B-Instruct-2507-GGUF Qwen3-4B-Instruct-2507-Q8_0.gguf
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```
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##### Flux
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```bash
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# flux2-klein
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# Capable of editing images in 4 steps (though 5 is my recommended steps)
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mkdir /home/ai/models/image/flux2-klein && cd /home/ai/models/image/flux2-klein
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hf download --local-dir . leejet/FLUX.2-klein-9B-GGUF flux-2-klein-9b-Q8_0.gguf
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hf download --local-dir . black-forest-labs/FLUX.2-dev ae.safetensors
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hf download --local-dir . unsloth/Qwen3-8B-GGUF Qwen3-8B-Q8_0.gguf
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```
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#### Embedding Models
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##### Nomic
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```bash
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# nomic-embed-text-v2
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mkdir /home/ai/models/embedding/nomic-embed-text-v2
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hf download --local-dir /home/ai/models/embedding/nomic-embed-text-v2 ggml-org/Nomic-Embed-Text-V2-GGUF
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```
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## llama.cpp
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<https://github.com/ggml-org/llama.cpp/tree/master/tools/server>
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```bash
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# Build the llama.cpp container image
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git clone https://github.com/ggml-org/llama.cpp.git
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cd llama.cpp
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export BUILD_TAG=$(date +"%Y-%m-%d-%H-%M-%S")
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# Vulkan (better performance as of Feb 2026)
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podman build -f .devops/vulkan.Dockerfile -t llama-cpp-vulkan:${BUILD_TAG} -t llama-cpp-vulkan:latest .
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# ROCM
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podman build -f .devops/rocm.Dockerfile -t llama-cpp-rocm:${BUILD_TAG} -t llama-cpp-rocm:latest .
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# Run llama demo server (Available on port 8000)
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podman run \
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--rm \
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--name llama-server-demo \
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--device=/dev/kfd \
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--device=/dev/dri \
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-v /home/ai/models/text:/models:z \
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-p 8000:8000 \
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localhost/llama-cpp-vulkan:latest \
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--host 0.0.0.0 \
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--port 8000 \
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-c 32768 \
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--perf \
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--n-gpu-layers all \
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--jinja \
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--models-max 1 \
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--models-dir /models
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```
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## stable-diffusion.cpp
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Server: <https://github.com/leejet/stable-diffusion.cpp/tree/master/examples/server>
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CLI: <https://github.com/leejet/stable-diffusion.cpp/tree/master/examples/cli>
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```bash
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git clone https://github.com/leejet/stable-diffusion.cpp.git
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cd stable-diffusion.cpp
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git submodule update --init --recursive
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export BUILD_TAG=$(date +"%Y-%m-%d-%H-%M-%S")
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# Vulkan
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podman build -f Dockerfile.vulkan -t stable-diffusion-cpp:${BUILD_TAG} -t stable-diffusion-cpp:latest .
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```
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```bash
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# Generate an image with z-turbo
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podman run --rm \
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-v /home/ai/models:/models:z \
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-v /home/ai/output:/output:z \
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--device /dev/kfd \
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--device /dev/dri \
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localhost/stable-diffusion-cpp:latest \
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--diffusion-model /models/image/z-turbo/z_image_turbo-Q8_0.gguf \
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--vae /models/image/z-turbo/ae.safetensors \
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--llm /models/image/z-turbo/Qwen3-4B-Instruct-2507-Q8_0.gguf \
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-v \
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--cfg-scale 1.0 \
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--vae-conv-direct \
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--diffusion-conv-direct \
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--fa \
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--mmap \
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--seed -1 \
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--steps 8 \
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-H 1024 \
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-W 1024 \
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-o /output/output.png \
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-p "A photorealistic dragon"
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# Edit the generated image with flux2-klein
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podman run --rm \
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-v /home/ai/models:/models:z \
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-v /home/ai/output:/output:z \
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--device /dev/kfd \
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--device /dev/dri \
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localhost/stable-diffusion-cpp:latest \
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--diffusion-model /models/image/flux2-klein/flux-2-klein-9b-Q8_0.gguf \
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--vae /models/image/flux2-klein/ae.safetensors \
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--llm /models/image/flux2-klein/Qwen3-8B-Q8_0.gguf \
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-v \
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--cfg-scale 1.0 \
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--sampling-method euler \
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--vae-conv-direct \
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--diffusion-conv-direct \
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--fa \
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--mmap \
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--steps 5 \
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-H 1024 \
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-W 1024 \
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-r /output/output.png \
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-o /output/edit.png \
|
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-p "Replace the dragon with an old car"
|
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```
|
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|
||||
## open-webui
|
||||
|
||||
```bash
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||||
mkdir /home/ai/.env
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||||
# Create a file called open-webui-env with `WEBUI_SECRET_KEY="some-random-key"
|
||||
scp active/device_framework_desktop/secrets/open-webui-env deskwork-ai:.env/
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||||
|
||||
# Will be available on port 8080
|
||||
podman run \
|
||||
-d \
|
||||
-p 8080:8080 \
|
||||
-v open-webui:/app/backend/data \
|
||||
--name open-webui \
|
||||
--restart always \
|
||||
ghcr.io/open-webui/open-webui:main
|
||||
```
|
||||
|
||||
Use the following connections:
|
||||
|
||||
| Service | Endpoint |
|
||||
| ------------------------- | ----------------------------------------- |
|
||||
| llama.cpp | <http://host.containers.internal:8000> |
|
||||
| stable-diffusion.cpp | <http://host.containers.internal:1234/v1> |
|
||||
| stable-diffusion.cpp edit | <http://host.containers.internal:1235/v1> |
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||||
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||||
## Install Services with Quadlets
|
||||
|
||||
### Internal and External Pods
|
||||
|
||||
These will be used to restrict internet access to our llama.cpp and
|
||||
stable-diffusion.cpp services while allowing the frontend services to
|
||||
communicate with those containers.
|
||||
|
||||
```bash
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||||
scp -r active/device_framework_desktop/quadlets_pods/* deskwork-ai:.config/containers/systemd/
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||||
ssh deskwork-ai
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||||
systemctl --user daemon-reload
|
||||
systemctl --user start ai-internal-pod.service ai-external-pod.service
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||||
```
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||||
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||||
### Llama CPP Server
|
||||
|
||||
Installs the llama.cpp server to run our text models.
|
||||
|
||||
```bash
|
||||
scp -r active/device_framework_desktop/quadlets_llama_server/* deskwork-ai:.config/containers/systemd/
|
||||
ssh deskwork-ai
|
||||
systemctl --user daemon-reload
|
||||
systemctl --user restart ai-internal-pod.service
|
||||
```
|
||||
|
||||
### Stable Diffusion CPP
|
||||
|
||||
Installs the stable-diffusion.cpp server to run our image models.
|
||||
|
||||
```bash
|
||||
scp -r active/device_framework_desktop/quadlets_stable_diffusion/* deskwork-ai:.config/containers/systemd/
|
||||
ssh deskwork-ai
|
||||
systemctl --user daemon-reload
|
||||
systemctl --user restart ai-internal-pod.service
|
||||
```
|
||||
|
||||
### Open Webui
|
||||
|
||||
Installs the open webui frontend.
|
||||
|
||||
```bash
|
||||
scp -r active/device_framework_desktop/quadlets_openwebui/* deskwork-ai:.config/containers/systemd/
|
||||
ssh deskwork-ai
|
||||
systemctl --user daemon-reload
|
||||
systemctl --user restart ai-external-pod.service
|
||||
```
|
||||
|
||||
Note, all services will be available at `host.containers.internal`. So llama.cpp
|
||||
will be up at `http://host.containers.internal:8000`.
|
||||
|
||||
### Install the update script
|
||||
|
||||
```bash
|
||||
# 1. Builds the latest llama.cpp and stable-diffusion.cpp
|
||||
# 2. Pulls the latest open-webui
|
||||
# 3. Restarts all services
|
||||
scp active/device_framework_desktop/update-script.sh deskwork-ai:
|
||||
ssh deskwork-ai
|
||||
chmod +x update-script.sh
|
||||
./update-script.sh
|
||||
```
|
||||
|
||||
### Install Guest Open Webui with Start/Stop Services
|
||||
|
||||
Optionally install a guest openwebui service.
|
||||
|
||||
```bash
|
||||
scp -r active/device_framework_desktop/systemd/. deskwork-ai:.config/systemd/user/
|
||||
ssh deskwork-ai
|
||||
systemctl --user daemon-reload
|
||||
systemctl --user enable open-webui-guest-start.timer
|
||||
systemctl --user enable open-webui-guest-stop.timer
|
||||
```
|
||||
|
||||
## Benchmark Results
|
||||
|
||||
Benchmarks are run with [unsloth gpt-oss-20b Q8_0](https://huggingface.co/unsloth/gpt-oss-20b-GGUF/blob/main/gpt-oss-20b-Q8_0.gguf)
|
||||
|
||||
```bash
|
||||
# Run the llama.cpp pod (AMD)
|
||||
podman run -it --rm \
|
||||
--device=/dev/kfd \
|
||||
--device=/dev/dri \
|
||||
-v /home/ai/models/text:/models:z \
|
||||
--entrypoint /bin/bash \
|
||||
ghcr.io/ggml-org/llama.cpp:full-vulkan
|
||||
|
||||
# Benchmark command
|
||||
./llama-bench -m /models/benchmark/gpt-oss-20b-Q8_0.gguf
|
||||
```
|
||||
|
||||
Framework Desktop
|
||||
|
||||
| model | size | params | backend | ngl | test | t/s |
|
||||
| ---------------- | --------: | ------: | ------- | ---: | ----: | -------------: |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | Vulkan | 99 | pp512 | 1128.50 ± 7.60 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | Vulkan | 99 | tg128 | 77.94 ± 0.08 |
|
||||
|
||||
| model | size | params | backend | ngl | test | t/s |
|
||||
| ---------------- | --------: | ------: | ------- | ---: | ----: | ------------: |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | ROCm | 99 | pp512 | 526.05 ± 7.04 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | ROCm | 99 | tg128 | 70.98 ± 0.01 |
|
||||
|
||||
AMD R9700
|
||||
|
||||
| model | size | params | backend | ngl | test | t/s |
|
||||
| ---------------- | --------: | ------: | ------- | ---: | ----: | ---------------: |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | Vulkan | 99 | pp512 | 3756.79 ± 203.97 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | Vulkan | 99 | tg128 | 174.24 ± 0.32 |
|
||||
|
||||
NVIDIA GeForce RTX 4080 SUPER
|
||||
|
||||
| model | size | params | backend | ngl | test | t/s |
|
||||
| ---------------- | --------: | ------: | ------- | ---: | ----: | ------------: |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | CUDA | 99 | tg128 | 193.28 ± 1.03 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | CUDA | 99 | tg256 | 193.55 ± 0.34 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | CUDA | 99 | tg512 | 187.39 ± 0.10 |
|
||||
|
||||
NVIDIA GeForce RTX 3090
|
||||
|
||||
| model | size | params | backend | ngl | test | t/s |
|
||||
| ---------------- | --------: | ------: | ------- | ---: | ----: | --------------: |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | CUDA | 99 | pp512 | 4297.72 ± 35.60 |
|
||||
| gpt-oss 20B Q8_0 | 11.27 GiB | 20.91 B | CUDA | 99 | tg128 | 197.73 ± 0.62 |
|
||||
Reference in New Issue
Block a user