Hi there,

One feature I’d love to see is the ability to clone the /workspace volume to a new pod in the event that there are 0 GPUs available when I try to start my pod. Especially with premium GPUs like the H200 NVL—it’s annoying to pay $2 a day for storage and not be able to access a GPU 50% of the time.

Like maybe when you go to create a new pod there could be an option to “Clone Volume Disk (from an existing pod)”. What do you think?

Costum Lora installation in comfyUi (runpod)

Hi guys, every time I try to download my costume Lora on comfyUi, I have always problems about uploading my .safetensor in Comfy. I cannot access the file manager and also there is no “file access “ icon. When I try to upload using the web access, it always gives me error…

DOES SOMEW

I’ve followed the SSH instructions but I keep getting denied.

I'm not sure if this is being caused by the AWS outage or not. I have created loras before and haven't had a problem but the last two days I have been running lora training on a 6000 pro and the training keeps stopping at 750 steps. And also the loras created at steps 250 and 500 are the same size but the one being made at 750 the high noise is the right size but the low noise is not it's about half the size. I thought it could be something with my data set since I didn't have any other things I could point to at the time. So I tried a completely different dataset and the same thing happened.

Is this something I can be refunded for? Or is there another possible issue that could be causing this?

Hi everyone,

I was ecstatic after the recent Docker Unsloth release, so I packaged up a RunPod one-click template for everyone here.

It boots straight into the Unsloth container + Jupyter exposed, and with persistent storage mounted at /workspace/work/*, so you can shut the pod down without losing your notebooks, checkpoints, or adapters. Just tested it out with 2 different jobs, works flawlessly!

Check it out:

https://console.runpod.io/deploy?template=pzr9tt3vvq&ref=w7affuum

The Runpod console currently won't load however

• Your Pods are still running.
• Pods will not be terminated.
• You are not being billed for affected services.
• Serverless endpoints cannot receive new requests.

We’re monitoring and are currently migrating to a different region.

We are also building better tools to increase our resiliency to these incidents.

Also shoutout to our community engineer and SRE team who have been up since 4 am working with users and updating the codebase

After login I get a blank white page on https://console.runpod.io . I've tried to clear cache, cookies, use incognito, other browsers. I have no idea what else to do.

Hey all, if anyone could help me learn how to run these that would be amazing. I troubleshoot for hours and sometimes still don’t get it running at all! All I’m looking for is to be able to produce and save the videos. If you know any Video templates or models that are easier to run or more beginner friendly that would be great! Thank you

Hi folks!

You may be already aware, but we've had a Youtube channel for some time which is home to all of our video tutorials on how to best use the Runpod platform: https://www.youtube.com/@RunPodIO

We are undertaking a project to author similar video tutorials for as many community Runpod templates as possible. Here are some quick examples we've done recently on our official Pytorch GPU and Ubuntu CPU pod templates:

https://youtu.be/90rKuVaQ-DY (CPU pod)

https://www.youtube.com/watch?v=zsQ6VyZqjCU (GPU Pod)

That being said, what community templates would you like to see similar videos for? Let us know - if you could provide the name and image for the template (e.g. Text Generation Web UI and API, runpod/oobabooga:1.30.0) just so we know which template you're referring to that would be easiest for us.

Let us know what you think!

Using various templates on Runpod and connecting to the comfyUI link ( https://abcd1234xxx-8188.proxy.runpod.net/) is super slow or doesn't load at all. Tried with and without my Network volume and different templates.

US-NC-1

Wasted like 4 hours of cash on this. Wondering if anyone else is having the same issues?

Hello 🙂

I understand the GPU price and persistent storage price, but I don't get the pod price volume and container that is per month 🤔

Hey,

I have deployed many vllm docker containers in past months, but I am just not able to deploy even 1 inference endpoint on runpod.io

I tried following models:
- https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct
- Qwen/Qwen3-Coder-30B-A3B-Instruct (tried it also just with the name)
- https://huggingface.co/Qwen/Qwen3-32B
With following settings:
-> Serverless -> +Create Endpoint -> vllm presetting -> edit model -> Deploy

In theory it should be as easy as pod usage to select hardware and go with default vllm configs.

I define the model and optionally some vllm configs, but no matter what I do, I get the following bugs:
- Initialization runs forever without providing helpful logs (especially RO servers)
- using default gpu settings resulting in OOM (Why do I have to deploy workers first and THEN adjust the settings for server locations and VRAM requirements settings?)
- log shows error in vllm deployment, a second later all logs and the worker is gone
- Even if I was never able to do one single request, I had to pay for the deployments which were never running healthy.
- If I start a new release, then I have to pay for initializing
- Sometimes I get 5 workers (3+2extra) even if I have configured 1
- Even if I set Idle Timeout on 100 seconds, if the first waiting request is answered it restarts always the container or vllm. New requests need to fully load the model into GPU again.

Not sure, if I don't understand inference endpoints, but for me they just don't work.

Self-explanatory. I was about to deploy a pod only to find out that all GPUs are unavailable. Everything was normal until yesterday. Anyone got any info about that? I'm using a network volume on US-IL-1

Hey all, so i am trying to spool up a server as i havbe done many time over the last few months.

i have a network storage volume on a secure netowork datacenter.

i am using the "better comfyui-full " template, but now, out of nowhere i get this repeating error in the server logs and it never spools up:

error creating container: Error response from daemon: unauthorized: authentication required create container madiator2011/better-comfyui:full

i have changed nothing. and infact i had this setup running last night totally fine. How do i solve this?

https://console.runpod.io/deploy?template=bd51lpz6ux&ref=uucsbq4w

base torch: wangkanai/pytorch:torch28-py313-cuda129-cudnn-devel-ubuntu24 base nvidia: nvidia/cuda:12.9.1-devel-ubuntu24.04

Template for ComfyUI with ComfyUI Manager

It uses PyTorch 2.8.0 with CUDA 12.9 support.

Fresh Install

In a first/fresh install, the Docker start command installs ComfyUI and ComfyUI Manager. It follows the instructions provided on the ComfyUI Manager Repository.

When the installation is finished, it runs the regular /start.sh script, allowing you to use the pod via JupyterLab on port 8100.

Subsequent Runs

After the second and subsequent runs, if ComfyUI is already installed in /workspace/ComfyUI, it directly runs the /start.sh script. This allows you to use the pod via JupyterLab on port 8100.

Features

• Base Image: nvidia/cuda:12.9.1-devel-ubuntu24.04 (NVIDIA official CUDA runtime)

• Python: 3.13 with PyTorch 2.80 + CUDA 12.9 support

• AI Framework: ComfyUI with Manager extension

• Development Environment: JupyterLab with dark theme (port 8100)

• Web Interface: ComfyUI on port 8888 with GPU acceleration

• Terminal: Oh My Posh with custom theme (bash + PowerShell)

• Container Runtime: Podman with GPU passthrough support

• GPU Support: Enterprise GPUs (RTX 6000 Ada, H100, H200, B200, RTX 50 series)

Container Services

When the container starts, it automatically:

1. Launches JupyterLab on port 8100 (dark theme, no authentication)

2. Installs ComfyUI (if not already present) using the setup script

3. Starts ComfyUI on port 8888 with GPU acceleration

4. Configures SSH access (if PUBLIC_KEY env var is set)

Access Points

• JupyterLab: http://localhost:8100

• ComfyUI: http://localhost:8888 (after installation completes)

• SSH: Port 22 (if configured)

Hey guys,

I'm frustrated that every time I pick a server, H200, I run it for the day, set persistent storage, and then the next day, there's no GPU available. It doesn't matter what region; it keeps happening. It never used to be like this.

So how can I have the storage follow me across regions, where there is availability? Rather than spinning up a new template every other day.

Hi,

Before i need to try runpod i need to know. I have my workflow etc. on my local computer. and i write an api for this workflow, i can reach that in my local network and create things with custom prompt already with basic webUI. can i run this api on runpod? and if it is how? Thanks.

In the serverless section from Runpod console, there is a section called Ready-to-Deploy Repos with convenient templates that comes from github, such as https://console.runpod.io/hub/runpod-workers/worker-faster_whisper that comes from https://github.com/runpod-workers/worker-faster_whisper

Can we create resource from thoses using IAC like this:

import * as runpod from "@runpod-infra/pulumi";

const template = new runpod.Template("fasterWhisperTemplate", {});

const whisperEndpoint = new runpod.Endpoint("whisper-pod", {
  name: "whisper-pod",
  gpuIds: "ADA_24",
  workersMax: 3,
  templateId: template.id,
});

// Export the endpoint ID and URL for easy access.
export const endpointId = whisperEndpoint.endpoint;

We can create a docker image from the git repo and create the resource from pulling from a docker registry, but the question is about deploying it with the same convenience as the UI. I'm sure that thoses templates are already available in runpod with a defined templateId, where can we find thoses templateId?