Use the comparison tool below to compare the top AI Infrastructure platforms on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Foundry
Foundry
Foundry is the next generation of public cloud powered by an orchestration system that makes it as simple as flicking a switch to access AI computing. Discover the features of our GPU cloud service designed for maximum performance. You can use our GPU cloud services to manage training runs, serve clients, or meet research deadlines. For years, industry giants have invested in infra-teams that build sophisticated tools for cluster management and workload orchestration to abstract the hardware. Foundry makes it possible for everyone to benefit from the compute leverage of a twenty-person team. The current GPU ecosystem operates on a first-come-first-served basis and is fixed-price. The availability of GPUs during peak periods is a problem, as are the wide differences in pricing across vendors. Foundry's price performance is superior to anyone else on the market thanks to a sophisticated mechanism. -
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Lumino
Lumino
The first hardware and software computing protocol that integrates both to train and fine tune your AI models. Reduce your training costs up to 80%. Deploy your model in seconds using open-source template models or bring your model. Debug containers easily with GPU, CPU and Memory metrics. You can monitor logs live. You can track all models and training set with cryptographic proofs to ensure complete accountability. You can control the entire training process with just a few commands. You can earn block rewards by adding your computer to the networking. Track key metrics like connectivity and uptime. -
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Bright for Deep Learning
Nvidia
Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).