How to List RTX 4070 on RunPod

How to List RTX 4070 on RunPod | Generated by AI

Home 2026.06

Question: How do I list my RTX 4070 GPU machine on RunPod so others can rent it?

Answer:

RunPod has a Secure Cloud (their own DCs) and Community Cloud (your hardware). You want the Community Cloud host program.

Requirements

Linux host (Ubuntu 20.04+ recommended)
Static or stable public IP
Docker installed
NVIDIA drivers + nvidia-container-toolkit
Ports open: 22, 8888, 2222, 443, and a range for pod forwarding

Steps

1. Install RunPod host daemon

# Install dependencies
curl -fsSL https://get.docker.com | sh
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list \
  | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

# Verify GPU visible to Docker
docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi

Go to: https://www.runpod.io/console/host/machines → “List a GPU”

You’ll need:

RunPod account with billing/payout setup (Stripe)
Your machine’s public IP

3. Run the host agent

RunPod gives you a one-liner after registration — looks like:

sudo docker run -d \
  --name runpod-host \
  --restart always \
  --privileged \
  --network host \
  -v /var/run/docker.sock:/var/run/docker.sock \
  -e RUNPOD_API_KEY=<API_KEY> \
  runpod/host-agent:latest

4. Configure pricing

In the dashboard, set:

GPU price ($/hr) — RTX 4070 community cloud goes ~$0.15–0.25/hr currently
Disk price
Min/Max pod duration

5. Firewall rules (ufw example)

sudo ufw allow 22/tcp
sudo ufw allow 443/tcp
sudo ufw allow 8888/tcp
sudo ufw allow 2222/tcp
sudo ufw allow 40000:60000/tcp  # pod port forwarding range

Caveats for Your Setup

Issue	Detail
Home ISP	Most residential ISPs block inbound ports or use CGNAT — check if you have a real public IP with `curl ifconfig.me` and test inbound connectivity
Dynamic IP	Use a DDNS service or pay for static IP; RunPod needs stable routing
Uptime expectation	Renters expect availability — RunPod tracks your uptime score
RTX 4070 12GB	Competes well for inference workloads (Mistral 7B, SDXL, Whisper) but won’t attract training jobs
Bandwidth	You pay egress on your home connection — high-bandwidth pods will eat your quota

Honest Assessment

For a home machine on residential internet, RunPod hosting is marginal:

CGNAT / dynamic IP is the biggest blocker
Revenue on a 4070 is low (~$2–5/day max if 100% utilized, rarely happens)
Your workstation at 192.168.1.36 is more valuable to you for local dev + your own inference

If you want passive GPU income, Vast.ai is often easier to set up for community hosting and has lower friction than RunPod for home hosts.

# Check if you have a real public IP (not CGNAT)
curl ifconfig.me
# Then check if port 22 is reachable from outside:
# Use https://portchecker.co or ask someone to nc -zv <your_ip> 22

References:

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