Linux Ollama

Linux Ollama — run Ollama on Linux with fleet routing across multiple Linux machines. Linux Ollama setup for Llama, Qwen, DeepSeek, Phi, Mistral. Route Ollama inference across Linux servers, desktops, and edge devices. Linux Ollama load balancing with systemd integration. Linux Ollama本地推理。Linux Ollama enrutador IA.

Linux Ollama — Fleet Routing for Ollama on Linux

Run Ollama on Linux with multi-machine load balancing. Linux Ollama Herd turns multiple Linux machines into one smart Ollama endpoint. Your server rack, your desktop, your edge device — all serving AI through one Linux Ollama URL.

Linux Ollama setup

Step 1: Install Ollama on Linux

bash

curl -fsSL https://ollama.ai/install.sh | sh

Step 2: Install Linux Ollama Herd

bash

pip install ollama-herd

Step 3: Start the Linux Ollama router

On one Linux machine (your router):

bash

herd          # starts Linux Ollama router on port 11435
herd-node     # registers this Linux machine

On every other Linux machine:

bash

herd-node     # auto-discovers the Linux Ollama router via mDNS

No mDNS? Connect Linux nodes directly: herd-node --router-url http://router-ip:11435

Linux Ollama systemd integration

Run Linux Ollama Herd as a systemd service for automatic startup:

bash

# /etc/systemd/system/ollama-herd.service
[Unit]
Description=Linux Ollama Herd Router
After=network.target ollama.service

[Service]
Type=simple
ExecStart=/usr/local/bin/herd
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target

bash

sudo systemctl enable ollama-herd
sudo systemctl start ollama-herd

Node agent as a Linux systemd service:

bash

# /etc/systemd/system/ollama-herd-node.service
[Unit]
Description=Linux Ollama Herd Node Agent
After=network.target ollama.service

[Service]
Type=simple
ExecStart=/usr/local/bin/herd-node
Restart=always
RestartSec=5

[Install]
WantedBy=multi-user.target

Use Linux Ollama

OpenAI SDK

python

from openai import OpenAI

# Your Linux Ollama fleet
client = OpenAI(base_url="http://localhost:11435/v1", api_key="not-needed")

response = client.chat.completions.create(
    model="llama3.3:70b",
    messages=[{"role": "user", "content": "Write a systemd service file for a Python API"}],
    stream=True,
)
for chunk in response:
    print(chunk.choices[0].delta.content or "", end="")

curl (Ollama format)

bash

# Linux Ollama inference
curl http://localhost:11435/api/chat -d '{
  "model": "qwen3.5:32b",
  "messages": [{"role": "user", "content": "Explain Linux process scheduling"}],
  "stream": false
}'

Linux Ollama environment setup

bash

# Optimize Linux Ollama performance via systemd
sudo systemctl edit ollama
# Add under [Service]:
#   Environment="OLLAMA_KEEP_ALIVE=-1"
#   Environment="OLLAMA_MAX_LOADED_MODELS=-1"
#   Environment="OLLAMA_NUM_PARALLEL=2"
sudo systemctl restart ollama

Or via shell profile:

bash

echo 'export OLLAMA_KEEP_ALIVE=-1' >> ~/.bashrc
echo 'export OLLAMA_MAX_LOADED_MODELS=-1' >> ~/.bashrc
source ~/.bashrc

Linux Ollama GPU support

Linux GPU	vRAM	Best Linux Ollama models
NVIDIA RTX 4090	24GB	llama3.3:70b, qwen3.5:32b
NVIDIA A100	40/80GB	deepseek-v3, qwen3.5:72b
NVIDIA L40S	48GB	llama3.3:70b (full precision)
AMD ROCm (experimental)	varies	Ollama ROCm support on Linux
CPU only	system RAM	phi4-mini, gemma3:1b — slower but works

Linux Ollama supports NVIDIA CUDA, experimental AMD ROCm, and CPU-only inference.

Linux Ollama firewall

bash

# UFW (Ubuntu/Debian)
sudo ufw allow 11435/tcp

# firewalld (RHEL/Fedora)
sudo firewall-cmd --add-port=11435/tcp --permanent
sudo firewall-cmd --reload

# iptables
sudo iptables -A INPUT -p tcp --dport 11435 -j ACCEPT

Monitor Linux Ollama

bash

# Linux Ollama fleet status
curl -s http://localhost:11435/fleet/status | python3 -m json.tool

# Linux Ollama health — 15 automated checks
curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool

# Models on Linux Ollama nodes
curl -s http://localhost:11435/api/ps | python3 -m json.tool

Dashboard at http://localhost:11435/dashboard — live Linux Ollama monitoring.

Linux Ollama logs

bash

# JSONL structured logs
tail -f ~/.fleet-manager/logs/herd.jsonl.$(date +%Y-%m-%d) | python3 -m json.tool

# Check for Linux Ollama errors
grep '"level":"ERROR"' ~/.fleet-manager/logs/herd.jsonl.$(date +%Y-%m-%d)

Also available on Linux Ollama

Image generation

bash

curl http://localhost:11435/api/generate-image \
  -d '{"model": "z-image-turbo", "prompt": "Linux penguin in cyberspace", "width": 1024, "height": 1024}'

Embeddings

bash

curl http://localhost:11435/api/embed \
  -d '{"model": "nomic-embed-text", "input": "Linux Ollama local inference"}'

Full documentation

• Agent Setup Guide
• API Reference

Contribute

Ollama Herd is open source (MIT). Linux Ollama users welcome:

• Star on GitHub
• Open an issue

Guardrails

• Linux Ollama model downloads require explicit user confirmation.
• Linux Ollama model deletion requires explicit user confirmation.
• Never delete or modify files in ~/.fleet-manager/.
• No models are downloaded automatically — all pulls are user-initiated or require opt-in.