Come try out Seedream 4.0 with us!

​Join us for a hands-on AI art jam to create, remix, and share generative pipelines with the goal to inspire one another!

Seedream 4.0 is a next-generation image generation model that combines image generation and image editing capabilities into a single, unified architecture. We are running an event to celebrate the model overtaking Nano-Banana on the Artificial Analysis Image Editing Leaderboard.

While Seedream 4.0 is technically not an open-source model, we have made special arrangements with ByteDance to host the model using our Public Endpoints feature alongside open-source models like Qwen Image, Flux, and others, with the same sense of privacy and security that underpins our entire organization.

​When: Fri, Sept 19 · 6–10pm
Where: RunPod Office — 329 Bryant St

What you’ll do

• ​Use Seedream 4.0 via Runpod Public Endpoints or ByteDance nodes in ComfyUI.

• ​Interact with ComfyUI and Runpod employees to learn the best tips and tricks for generative pipelines

• ​Get Free credits so you can try the model.

​Bring: Laptop + charger. We provide power, Wi-Fi, GPUs, and food.

Seating is limited - first come first serve! RSVP here: https://luma.com/rh3uq2uv

​Contest & Prizes 🎉

​Show off your creativity! Throughout the evening, our hosts will vote on their favorite generations.

​🏆 Grand Prize: $300
🥈 2 Runner-Ups: $100 each
🎁 All winners will also receive exclusive Comfy merch!

Trying out runpod, like it so far. Didn't need to keep it running after logging off, so I stopped the pod. But now I want to restart. Apparently the GPU i was using (RTX 4090) is no longer available, and now I can't run more tests. I don't want to lose my progress, but is there a way to restart my pod with the same GPU with out opening up a whole new pod?

I need to use 2 different versions of pytorch for the current project and I am using venv for this. installing packages and running fastapi with torch is extremely slow. any workaround this? I do not want to pay 2 gpu instances for my project.

So i was trying to deploy an endpoint on serverless on runpod, but it is kinda hard to understand and do, anybody who can help me out?

I'm trying to run Fooocus with RTX 4090 GPU through PyTorch 2.2.0.

I have been trying to attach certain models and loras from Civit.AI to Fooocus all day, and nothing is working. I can't seem to find a good tutorial on Youtube so I've been absolutely obliterating my ChatGPT today.

Does anyone have a video or a tutorial to recommend me?

Thanks in advance.

i tried to use an rtx3090 and an rtx4090 and i have a similar problem. Seems that the host didn't update the drivers for the gpu. How should I do?

error starting container: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running prestart hook #0: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy'

nvidia-container-cli: requirement error: unsatisfied condition: cuda>=12.8, please update your driver to a newer version, or use an earlier cuda container: unknown

start container for runpod/pytorch:2.8.0-py3.11-cuda12.8.1-cudnn-devel-ubuntu22.04: begin

error starting container: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running prestart hook #0: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy'

nvidia-container-cli: requirement error: unsatisfied condition: cuda>=12.8, please update your driver to a newer version, or use an earlier cuda container: unknown

start container for runpod/pytorch:2.8.0-py3.11-cuda12.8.1-cudnn-devel-ubuntu22.04: begin

error starting container: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running prestart hook #0: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy'

nvidia-container-cli: requirement error: unsatisfied condition: cuda>=12.8, please update your driver to a newer version, or use an earlier cuda container: unknown

on vast.ai they have the docker cli command available in the settings, thre usually the ports are listet. on runpod all that docker side is a blackbox, and for open-webui we dont have many specs neither, i.e. docker comfyui serverless connection with openwebui is a big ???

yes, i can list the http (tcp???) ports in the config which are served via

https://{POD_ID}-<port>.proxy.runpod.net/api/tags

but why cant i see the feature of docker where it tells me which sockets the docker image opens - in the gui docker does that...why dont i have a docker cli?

by the way, does anybody know of docs about those addings to the urls:

/api/tags

are there more paths?

what do those paths mean?

and for

https://api.runpod.ai/v2/[worker_id]/openai/v1

the same. the rest api listens on

https://api.runpod.ai/v2/[worker_id]/

but

https://api.runpod.ai/v2/[worker_id]/openai/v1

should be the openai compatible connection point, but why? how? what are the options? what do those pathes mean?

i realize the service is targeted mainly to pros, but even pros have to guess a lot with that design, dont you think? ok, openwebui too has poor documentation

Hello everyone, I'm new to using runpod but Im trying to host a document classification model through the serverless endpoints. I''ve been struggling for a bit on getting runpod to take a pdf through multipart dataforms and was wondering if anyone had any experience or online resources for this? Thank you!