UberLLM vs Runware
Runware runs many models on its own hardware and rents GPU capacity. UberLLM rents no GPUs: it is a marketplace that sends each request to the cheapest healthy seller for that model, with a per-request price cap and a 5% fee only when you add credit.
Right now UberLLM routes 455 models, 191 of them for images, video, music and speech.
UberLLM vs Runware, side by side
| UberLLM | Runware | |
|---|---|---|
| How you start | $5 minimum top-up, no subscription | Pay as you go; minimum top-up not publicly listed |
| Free to try | None, prepaid credit | $2 free credits for new users with a business email |
| Fee on top of model prices | None per request; 5% when you add credit | Not publicly listed |
| Works with the OpenAI SDK | Yes | Yes |
| Works with Claude Code and the Anthropic SDK | Yes | Yes |
| Chat and text models | Yes | Yes |
| Image models | Yes | Yes |
| Video models | Yes | Yes |
| Music models | Yes | Yes |
| Same model from many sellers | Yes | Not stated |
| Failed generations are free | Yes | Yes |
| No-code app (no programming) | No | No |
| Run it on your own servers | No | No |
Runware facts are from its own site as of 28 October 2026 (its pricing page). “Not stated” means Runware does not publish it. The two companies are independent; Runware is a trademark of its owner. UberLLM prices are live on the model board.
What Runware is
Runware is an AI inference platform that runs models on hardware it owns. It offers on-demand model APIs for image, video, audio, LLM and 3D, plus serverless GPUs and dedicated compute.
How you pay
Pay as you go: per generation, per token for LLMs, per second for video and serverless GPU, or per character for audio. Reserved GPU capacity and bare-metal clusters are available on a term, and high-volume customers can get custom pricing from sales.
What UberLLM is
A marketplace for unused AI compute. Each request goes to the cheapest healthy seller for that model, behind one OpenAI- and Anthropic-compatible key.
How you pay
Pay per use at the price shown for each model, with nothing added per request. A 5% fee applies only when you add credit. A generation that fails costs nothing.
Pick UberLLM if
Developers who want the lowest live price for chat, image, video and music models under one key, using the OpenAI or Anthropic SDK they already have.
Pick Runware if
Teams that want image, video and LLM inference on one provider's own hardware, with the option to reserve dedicated GPUs or run their own models.
What Runware does that UberLLM doesn’t
- Serverless GPUs and dedicated bare-metal clusters
- Upload and run your own models, containers or fine-tuned weights
- Runs open models on its own hardware
- 3D generation and media tools like upscaling and background removal
Switch in one line
Point the SDK you already use at UberLLM. The same key covers chat, images, video, music and speech.
from openai import OpenAI
client = OpenAI(
base_url="https://api.uberllm.dev/v1", # the only line that changes
api_key="ull_your_key_here",
)
resp = client.chat.completions.create(
model="deepseek/deepseek-v4-flash",
messages=[{"role": "user", "content": "Hello!"}],
)
# the same key makes images (and video, music, speech)
img = client.images.generate(
model="venice/nano-banana-pro",
prompt="a red apple on a white table",
)FAQ
Is UberLLM a Runware alternative?
For pay-per-use model calls, yes. Both cover chat, image, video and music, accept OpenAI and Anthropic request formats, and don't charge for failed generations. If you need dedicated GPUs or want to run your own model weights, Runware is the better fit.
How is UberLLM different from Runware?
UberLLM is a marketplace for unused AI compute: one API key, and each request goes to the cheapest healthy seller for the model. You can cap the price per request with provider.max_price. UberLLM does not rent GPUs, host your own models or offer fine-tuning.
Can I run my own fine-tuned model?
On Runware, yes: its dedicated inference can run open-weight or your own custom or fine-tuned models. UberLLM does not offer fine-tuning or dedicated deployments; it serves the models listed in its catalogue.