What you can do with Jarvislabs.ai?
- Launch an GPU/CPU powered instance.
- Pause the instance.
- Resume the instance.
- Resume it by changing the GPU type, scaling GPUs or storage.
- SSH to an instance.
- Run from your own docker image.
- Deploy your model using Flask/FastAPI
Pick a modern Nvidia GPU to power your Deep Learning
We support the latest GPU based on Nvidia Ampere architecture (2022), which are usually 1.3X - 3X times faster than GPUs based on Turing Architecture. A100 is the fastest GPU, followed by A6000 and A5000.
|A100 - 40GB||7||32GB||$2.39/hr||$0.99/hr||$360/week||$1200/month|
|A6000 - 48GB||7||32GB||$1.79/hr||$0.79/hr||$270/week||$900/month|
|A5000 - 24GB||7||32GB||$1.29/hr||$0.59/hr||$195/week||$650/month|
You can also choose GPU based on Nvidia Turing Architecture (2019), which offers similar performance like Nvidia V100 GPU.
|RTX 6000 - 24GB||7||32GB||$0.99/hr||$0.39/hr||$149/week||$500/month|
|RTX 5000 - 16GB||7||32GB||$0.49/hr||$0.19/hr||$75/week||$245/month|
Need any assistance, say 👋 Hi to the team using the chat option available on the website or drop us an email to firstname.lastname@example.org