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QDivZero
Deploy any Hugging Face model without managing GPUs
Most AI platforms give you a fixed list of models. QDivZero lets you choose your own. Paste a Hugging Face model ID and deploy it as a ready-to-use endpoint, without managing GPUs or servers. Run LLMs, image and video generation, audio, computer vision, or even biomolecular models. Compute scales on demand, with GPU usage billed by the second. No fixed model catalog, no idle hardware costs, and no infrastructure headaches.
Hey Product Hunt! 👋
We’re José and Marta, the team behind QDivZero. We’re building this from Spain, combining our backgrounds in infrastructure, mathematics, chemistry and machine learning.
We started QDivZero because we wanted more freedom to experiment with AI models without setting up the infrastructure from scratch each time. Hugging Face has an incredible range of models, but getting one running for a real project can still take considerable work.
With QDivZero, you can find a model, check its deployment compatibility and launch it through the platform. That includes language models, image and video generation, speech, computer vision, forecasting and molecular modeling. We handle GPU provisioning and inference orchestration, and model deployments are billed for compute.
If you’d like to try QDivZero, we’re offering free trial credits on request. Create an account at platform.qdiv0.com, then contact us through the support chat and ask for trial credits. We’ll add them to your account and help you get started.
We launched in late September, so this is still early. We’d love to hear what you find useful, where you get stuck and what you think is missing.
Which Hugging Face model would you like to try, and what would you use it for?
We’ll be here answering questions throughout the launch!
No comment highlights available yet. Please check back later!
About QDivZero on Product Hunt
“Deploy any Hugging Face model without managing GPUs”
QDivZero was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #390 on the daily leaderboard. Most AI platforms give you a fixed list of models. QDivZero lets you choose your own. Paste a Hugging Face model ID and deploy it as a ready-to-use endpoint, without managing GPUs or servers. Run LLMs, image and video generation, audio, computer vision, or even biomolecular models. Compute scales on demand, with GPU usage billed by the second. No fixed model catalog, no idle hardware costs, and no infrastructure headaches.
QDivZero was featured in Developer Tools (521.5k followers) and Artificial Intelligence (481.6k followers) on Product Hunt. Together, these topics include over 220.2k products, making this a competitive space to launch in.
Who hunted QDivZero?
QDivZero was hunted by José Carlos. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how QDivZero stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
José Carlos