NVIDIA NIM , part of NVIDIA AI Enterprise , is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing across the cloud, data center and workstations. Google Kubernetes Engine (GKE) is the only managed Kubernetes solution to offer orchestration for the broadest selection of high performance, cost-efficient AI inference accelerators powered by NVIDIA GPUs. Together, NVIDIA NIM and GKE provide an optimized inference platform that is operationally efficient. These prebuilt containers support a broad spectrum of AI models—from open-source community models to NVIDIA AI Foundation models , as well as custom AI models. NIM microservices are deployed with a single command for easy integration into enterprise-grade AI applications using standard APIs and just a few lines of code. Built on robust foundations including inference engines like Triton Inference Server, TensorRT, TensorRT-LLM, and PyTorch, NIM is engineered to facilitate seamless AI inferencing at scale, ensuring that you can deploy AI applications on Google Kubernetes Engine (GKE) with confidence. Take a look at all the NIM models here . A few of these popular NIMs are available as a quick to deploy option on this kubernetes application. NIM provides features like low latency, high throughput, function calling, metrics export, standard API, optimized profiles & enterprise support. For more information on latest features, sample tutorials of NIM check the NIM developer documentation. Getting started technical documentation for running NIM on GKE is available here . Free support for developers on NVIDIA NIM is available through the NVIDIA NIM Developer Forum Global enterprise support for NVIDIA NIM is included with NVIDIA AI Enterprise subscription Benefits of NVIDIA AI Enterprise Support include: Enterprise grade support and SLAs provided directly from NVIDIA Access to NVIDIA AI experts from 8am-5pm local business hours for guidance on configuration and performance Priority notifications for the latest security fixes and maintenance releases For additional support information please contact NVIDIA Terms of service: NVIDIA Software License Agreement Product-Specific Terms for NVIDIA AI Products NVIDIA Community Model License For Llama-3.1 models: Llama 3.1 Community License Agreement. Built with Llama. For Llama3 models: Meta Llama 3 Community License , Built with Meta Llama 3. For Mistral models: Apache 2.0 License . For Mixtral models: Apache 2.0 License . For E5-Large models: MIT license .
NVIDIA AI Enterprise is an end-to-end, cloud-native software platform that accelerates data science pipelines and streamlines development and deployment of production-grade co-pilots and other generative AI applications. This software platform includes easy-to-use microservices that provide optimized model performance with enterprise-grade security, support, and stability to ensure a smooth transition from prototype to production for enterprises that run their businesses on AI. NVIDIA AI Enterprise offers best-in-class development tools, frameworks, and pretrained models for AI practitioners and reliable management and orchestration for IT professionals to ensure performance, high availability, and security. What’s included: With NVIDIA AI Enterprise customers get support and access to the following: NVIDIA NIM and CUDA-X microservices, which provide an optimized runtime and easy to use building blocks to streamline generative AI development. NVIDIA NeMo, an end-to-end framework for organizations to easily customize pretrained NVIDIA AI Foundation models and select community models for domain-specific use cases based on business data. NVIDIA Riva, a GPU-accelerated multilingual speech and translation AI SDK. NVIDIA RAPIDS Accelerator for Apache Spark to speed up Apache Spark 3 data science pipelines and AI model training. Frameworks and tools to accelerate AI development and deployment, including PyTorch, TensorFlow, NVIDIA RAPIDS, TAO Toolkit, NVIDIA TensorRT, TensorRT-LLM, and NVIDIA Triton Inference Server. Healthcare-specific frameworks and applications including NVIDIA Clara MONAI and NVIDIA Clara Parabricks. NVIDIA AI Enterprise includes support for all NVIDIA AI software published on the NGC public catalog labeled with “NVIDIA AI Enterprise Supported.” The NVIDIA AI Enterprise marketplace offer also includes a VMI which provides a standard, optimized run time for easy access to the above mentioned NVIDIA AI Enterprise software and ensures development compatibility between clouds and on premises infrastructure. NVIDIA AI Enterprise VMI includes: NVIDIA AI Enterprise Catalog access script Ubuntu Server 22.04 NVIDIA vGPU Driver Docker-ce NVIDIA Container Toolkit Google Cloud CLI, NGC CLI Miniconda, JupyterLab (within conda base env), Git Contact NVIDIA to learn more about NVIDIA AI Enterprise on Google Cloud and for private pricing by filling out the form here. Link For information on documentation, please refer: Quick Start Guide Release notes
Deploy a VM instance with NVIDIA’s VM image certified for maximum performance on NVIDIA GPUs, and easy access to NVIDIA NGC. The NVIDIA GPU-Optimized VMI is a virtual machine image for accelerating your Machine Learning, Deep Learning, Data Science and HPC workloads. Using this VMI, you can spin up a GPU-accelerated Compute Engine VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This VMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions. This GPU-optimized VMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. NVIDIA GPU-Optimized VMI includes: Ubuntu Server 22.04.3 LTS NVIDIA Driver 550.127.05 Docker-ce 27.3.1 NVIDIA Container Toolkit 1.16.2-1 Google Cloud CLI, NGC CLI 3.53.0 Miniconda, JupyterLab, Git For information on documentation and release notes please check NVIDIA GPU-Optimized VMI documentation
NVIDIA RTX Virtual Workstation software (formerly NVIDIA Quadro Virtual Data Center Workstation) enables users to run high-performance simulation, rendering, and design workloads from the cloud, with a native workstation-like performance. Using the NVIDIA Virtual Machine Image (VMI) with the RTX Virtual Workstation software in the Google Cloud Platform marketplace, customers can easily spin up a VM running on Windows Server 2019 in minutes. Easily configure with the NVIDIA GPU instance, vCPU, memory, and storage you need, without having to purchase any physical hardware and infrastructure. IT only needs to install applications and users are up and running. Benefits include: RTX Workstation Performance. NVIDIA GPUs power high-performance simulation, rendering, and design. Leverage RTX and NVIDIA Virtual GPU technology* with support for NVIDIA T4. ISV Certifications. Get proven NVIDIA RTX benefits from the cloud and leverage RTX ISV certifications. IT Speed and Agility. Spin up a GPU-accelerated virtual workstation in minutes, without having to manage endpoints or back-end infrastructure. Flexibility in the Cloud. Scale up and down as your business needs change and pay for only what you need based on hourly usage. Always-Up-to-Date. Your NVIDIA RTX Virtual Workstation image is always optimized with the latest patches and upgrades. Enterprise-Grade Security. Get the same RTX experience from anywhere, with the assurance that sensitive data is protected in the cloud with redundancy and compliance. Watch this video to see how you can deploy a cloud-based virtual workstation in 5 minutes: *Formerly known as NVIDIA GRID
Important: For step by step guide on how to setup this vm , please refer to our Getting Started guide Introducing NVIDIA GPU Cloud (NGC) Virtual Machine Solution: NVIDIA CUDA Suit VM Solution is tailored for developers, researchers, and enterprises seeking seamless access to NVIDIA's CUDA Toolkit, NVIDIA Nsight Compute, and NVIDIA Nsight Systems. This comprehensive solution offers a powerful ecosystem for GPU-accelerated computing, enabling users to harness the full potential of NVIDIA GPUs in the cloud environment without wasting their valuable time in installation & configuration. Key Features: 1. NVIDIA Drivers & preconfigured setup: Preinstalled NVIDIA drivers and all the NVIDIA utilities such as nvidia-smi as a foundation to exploit GPU capabilities & CUDA development . Users can jumpstart their GPU-accelerated projects without worrying about software dependencies or compatibility issues, streamlining & accelerating the development process. 2. CUDA Toolkit: The CUDA Toolkit is the core development tool for GPU-accelerated applications. With this solution, users gain access to the latest version of the CUDA Toolkit, empowering them to develop and optimize CUDA-accelerated applications efficiently. 3. NVIDIA Nsight Compute: Nsight Compute is a powerful profiler and performance analysis tool designed specifically for CUDA applications. With NGC Virtual Machine Solution, users can leverage Nsight Compute to deeply analyze the performance of their CUDA kernels, identify bottlenecks, and optimize their GPU-accelerated code for maximum efficiency. 4. NVIDIA Nsight Systems: Nsight Systems offers comprehensive system-wide performance analysis for GPU-accelerated applications. By integrating Nsight Systems into the NGC Virtual Machine Solution, users gain valuable insights into GPU utilization, memory bandwidth, and CPU-GPU interaction, enabling them to optimize the overall performance of their applications. 5. Cloud-Based Virtual Machine: The underlying scalable cloud-based infrastructure allows users to access NVIDIA GPU resources on-demand. Whether you're a small team or a large enterprise, you can quickly provision virtual machines with pre-installed CUDA Toolkit, Nsight Compute, and Nsight Systems, eliminating the need for manual setup and configuration. Disclaimer: Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and/or names or their products and are the property of their respective owners. We disclaim proprietary interest in the marks and names of others.
NVIDIA RTX Virtual Workstation software (formerly NVIDIA Quadro Virtual Data Center Workstation) enables users to run the high-performance simulation, rendering, and design workloads from the cloud, with a native workstation-like performance. Using the NVIDIA Virtual Machine Image (VMI) with the RTX Virtual Workstation software in the Google Cloud Platform marketplace, customers can easily spin up a VM running on Ubuntu 22.04 LTS in minutes. Easily configure with the NVIDIA GPU instance, vCPU, memory, and storage you need, without having to purchase any physical hardware and infrastructure. IT only needs to install applications and users are up and running. Benefits include: RTX Workstation Performance. NVIDIA GPUs power high-performance simulation, rendering, and design. Leverage RTX and NVIDIA Virtual GPU technology* with support for NVIDIA T4. ISV Certifications. Get proven NVIDIA RTX benefits from the cloud and leverage RTX ISV certifications. IT Speed and Agility. Spin up a GPU-accelerated virtual workstation in minutes, without having to manage endpoints or back-end infrastructure. Flexibility in the Cloud. Scale up and down as your business needs change and pay for only what you need based on hourly usage. Always-Up-to-Date. Your NVIDIA RTX Virtual Workstation image is always optimized with the latest patches and upgrades. Enterprise-Grade Security. Get the same RTX experience from anywhere, with the assurance that sensitive data is protected in the cloud with redundancy and compliance. Watch this video to see how you can deploy a cloud-based virtual workstation in 5 minutes: *Formerly known as NVIDIA GRID
NVIDIA RTX Virtual Workstation software (formerly NVIDIA Quadro Virtual Data Center Workstation) enables users to run the high-performance simulation, rendering, and design workloads from the cloud, with a native workstation-like performance. Using the NVIDIA Virtual Machine Image (VMI) with the RTX Virtual Workstation software in the Google Cloud Platform marketplace, customers can easily spin up a VM running on Ubuntu 22.04 LTS in minutes. Easily configure with the NVIDIA GPU instance, vCPU, memory, and storage you need, without having to purchase any physical hardware and infrastructure. IT only needs to install applications and users are up and running. Benefits include: RTX Workstation Performance. NVIDIA GPUs power high-performance simulation, rendering, and design. Leverage RTX and NVIDIA Virtual GPU technology* with support for NVIDIA T4. ISV Certifications. Get proven NVIDIA RTX benefits from the cloud and leverage RTX ISV certifications. IT Speed and Agility. Spin up a GPU-accelerated virtual workstation in minutes, without having to manage endpoints or back-end infrastructure. Flexibility in the Cloud. Scale up and down as your business needs change and pay for only what you need based on hourly usage. Always-Up-to-Date. Your NVIDIA RTX Virtual Workstation image is always optimized with the latest patches and upgrades. Enterprise-Grade Security. Get the same RTX experience from anywhere, with the assurance that sensitive data is protected in the cloud with redundancy and compliance. Watch this video to see how you can deploy a cloud-based virtual workstation in 5 minutes: *Formerly known as NVIDIA GRID
The NVIDIA cuQuantum Appliance is a highly performant multi-GPU multi-node solution for quantum circuit simulation. It contains NVIDIA’s cuStateVec and cuTensorNet libraries which optimize state vector and tensor network simulation, respectively. The cuTensorNet library functionality is accessible through Python for Tensor Network operations. With the cuStateVec libraries, NVIDIA provides the following simulators: IBM’s Qiskit Aer frontend via cusvaer, NVIDIA’s distributed state vector backend solver. a multi-GPU-optimized Google Cirq frontend via qsim, Google’s state vector simulator. NVIDIA cuQuantum Appliance VMI includes: NVIDIA cuQuantum Appliance Docker Container Ubuntu Server 20.04 NVIDIA Driver Docker-ce NVIDIA Container Toolkit Google Cloud CLI, NGC CLI Miniconda, JupyterLab, Git
The NVIDIA HPC SDK is a comprehensive suite of compilers, libraries and tools essential to maximizing developer productivity and the performance and portability of HPC applications. The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC directives, and CUDA. GPU-accelerated math libraries maximize performance on common HPC algorithms, and optimized communications libraries enable standards-based multi-GPU and scalable systems programming. Performance profiling and debugging tools simplify porting and optimization of HPC applications, and containerization tools enable easy deployment on-premises or in the cloud. Key features of the NVIDIA HPC SDK for Linux include: - Support for NVIDIA Ampere Architecture GPUs with FP16, TF32 and FP64 tensor cores - NVC++ ISO C++17 compiler with Parallel Algorithms acceleration on GPUs, OpenACC and OpenMP - NVFORTRAN ISO Fortran 2003 compiler with array intrinsics acceleration on GPUs, CUDA Fortran, OpenACC and OpenMP - NVC ISO C11 compiler with OpenACC and OpenMP - NVCC NVIDIA CUDA C++ compiler - NVIDIA Math Libraries including cuBLAS, cuSOLVER, cuSPARSE, cuFFT, cuTENSOR and cuRAND - Thrust, CUB, and libcu++ GPU-accelerated libraries of C++ parallel algorithms and data structures - NCCL, NVSHMEM and Open MPI libraries for fast multi-GPU/multi-node communications - NVIDIA Nsight Systems/Compute for interactive HPC applications performance profiler
NVIDIA® Riva is a set of GPU-accelerated multilingual speech and translation microservices for building fully customizable, real-time conversational AI pipelines. Riva includes automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT) and is deployable in all clouds, in data centers, at the edge, or on embedded devices. With Riva, organizations can add speech and translation capabilities with large language models (LLMs) and retrieved-augmented generation (RAG) to transform chatbots into powerful multilingual assistants and avatars. Riva is part of the NVIDIA AI Enterprise software platform.
DGX Cloud is an AI platform for enterprise developers offering a serverless experience. It is co-engineered with Google Cloud, integrating best of breed architectures and the newest NVIDIA AI technologies across accelerated computing, network fabric, software, and direct access to NVIDIA AI experts who get better results faster. DGX Cloud delivers industry-leading utilization efficiency with scale and productive work capacity for enterprise developers. DGX Cloud includes NVIDIA AI Enterprise offering accelerated data science libraries, optimized frameworks and pre-trained models that give developers a faster, easier, more productive experience that delivers production-ready models sooner. Benefits: Get the latest NVIDIA AI Technology First- Get our most advanced GPUs and infrastructure design delivered first on DGX Cloud. Google Cloud Supercharged with NVIDIA AI - Co-engineered with Google and NVIDIA to deliver a best of breed AI developer platform. Your Own AI Factory- Get in, work, get on your way to better AI apps sooner. Get Unstuck- Direct access to NVIDIA AI experts, 24/7 business-critical support, a designated technical account manager, and customer service success manager.
Important : For step by step guide on how to setup this vm , please refer to our Getting Started guide Experience the future of AI/ML development with our NVIDIA GPU-accelerated virtual machine offer. Key Features: 1. CUDA Toolkit from NVIDIA which provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime. 2. NVIDIA GPU Acceleration: Unlock unparalleled computing power with our optimized NVIDIA GPU driver setup. Experience lightning-fast performance and accelerated computing for even the most complex AI/ML tasks, enabling you to train & inference LLM models faster and to handle larger datasets with ease. 3. AI Extensions : Take your AI/ML projects to the next level with Jupyter AI extensions. Seamlessly integrate with over 100 pre-trained models like OpenAI/ChatGPT, GeminiOpenLLM & lot more to unlock new possibilities in LLM & generative AI. 4. JupyterHub Collaboration: Collaborate effortlessly with colleagues and teammates using JupyterHub's multi-user environment. Share code, data, and insights in real-time, driving innovation and efficiency across your team. 5. Comprehensive Library Support: Say goodbye to time consuming & tedious library installations - our virtual machine comes pre-configured with all the essential AI/ML libraries you need from TensorFlow to PyTorch and beyond, access the tools you love right out of the box. For step by step guide please visit- Getting Started Guide Disclaimer: Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and/or names or their products and are the property of their respective owners. We disclaim proprietary interest in the marks and names of others.
A pre-configured and fully integrated software stack with PyTorch, an open source machine learning library, and Python 3.6. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on NVidia GPU. The stack includes CUDA, a parallel computing platform and API model; and cuDNN, a GPU-accelerated library of primitives for deep neural networks. It also includes NVidia drivers and Development preset, program development and building tools, including C compiler, make etc.
Deploy a Compute Engine instance with your favorite machine learning framework, Intel(R) optimized for GCE and configured to support common GPU workloads out of the box. This deployment automates out the hassle of setting up a high-performance computing environment: the latest NVIDIA GPU libraries (CUDA, CuDNN, NCCL), latest Intel(R) libraries (Intel(R) MKL-DNN) are all ready to go, along with the latest supported drivers. Deep Learning VM supports for Python 3.7, Python 3.10 on Debian 10 or Debian 11. Choice of frameworks include Tensorflow 2.12, Tensorflow 2.11, Tensorflow 2.10, TensorFlow Enterprise 2.8.3, TensorFlow Enterprise 2.6.5, TensorFlow Enterprise 2.3.4, PyTorch 2.0, PyTorch 1.13, PyTorch 1.12, and R. Other frameworks can be installed on top of the CUDA 11.0/11.3/11.8 Intel(R) optimized base images, which include the common set of NVIDIA and Python libraries and set of Intel(R) optimized ML packages.
Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category. Jointly developed with Nvidia. This collaboration has resulted in a powerful 12B model that pushes the boundaries of language understanding and generation. Multilingual proficiency. Mistral Nemo is equipped with a new tokenizer, Tekken, designed for multilingual applications. It supports over 100 languages, including but not limited to English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch, Polish, and many more. Tekken has proven to be more efficient than the Llama 3 tokenizer in compressing text for approximately 85% of all languages, with significant improvements in Malayalam, Hindi, Arabic, and prevalent European languages. Agent-centric. Mistral Nemo possesses top-tier agentic capabilities, including native function calling and JSON outputting. Advanced Reasoning. Mistral Nemo demonstrates state-of-the-art mathematical and reasoning capabilities within its size category. Context length: Mistral Nemo supports a context length of 128K. Number of parameters: Mistral Nemo is a 12B model, making it a powerful drop-in replacement for any system using Mistral 7B, which it supersedes. Input: Models input text only. Output: Models generate text only.
ParaTools Pro for E4S™[1] - the Extreme-scale Scientific Software Stack[2] hardened for commercial clouds and supported by ParaTools, Inc. provides a platform for developing and deploying HPC and AI/ML applications. It features a performant remote desktop environment (based on VNC) on the login node and compute nodes interconnected by a low-latency, high bandwidth network adapter based on Google's custom Intel Infrastructure Processing Unit (IPU). ParaTools Pro for E4S™ features a suite of over 100 HPC tools built using the Spack[3] package manager and the proprietary MVAPICH MPI tuned for IPU. It features ready to use HPC applications (such as OpenFOAM, LAMMPS, Xyce, CP2K, deal.II, GROMACS, Quantum Espresso) as well as AI/ML tools based on Python (such as NVIDIA NeMo™, TensorFlow, PyTorch, JAX, Horovod, Keras, OpenCV, matplotlib, and supports Jupyter notebooks) and the Codium IDE. New packages can be easily installed using Spack and pip and are accessible on the cluster compute and login nodes. It may be used for developing the next generation of generative AI applications using a suite of Python tools and interfaces. E4S™ has built a unified computing environment for deployment of open-source projects. E4S™ was originally developed to provide a common software environment for the exascale leadership computing systems currently being deployed at DOE National Laboratories across the U.S. Support for ParaTools Pro for E4S™ is available through ParaTools, Inc. This product has additional charges associated with it for optional product support and updates. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Office of Advanced Scientific Computing and Research (ASCR), under SBIR Award Number DE-SC0022502 ("E4S: Extreme-Scale Scientific Software Stack for Commercial Clouds"). Note: This product contains repackaged and tuned open source software (e.g., E4S™, Spack and AI/ML tools like NVIDIA NeMo™, Horovod, JAX, Keras etc.) which is configured and linked against a proprietary MVAPICH MPI implementation specifically developed and tuned for IPU. [1]: https://www.paratools.com/ParaToolsPro [2]: https://e4s-project.github.io/ [3]: https://spack.io
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Hugging Face Generative AI Microservices (HUGS Inference) empowers you to rapidly deploy and scale open-source generative AI models with zero configuration. Leveraging optimized inference engines for leading hardware like NVIDIA GPUs, AMD GPUs, Intel GPUs, and Google TPUs. HUGS delivers unparalleled performance. Seamlessly integrate models via the industry-standard OpenAI API, simplifying development with tools like LangChain and LlamaIndex. Focus on building cutting-edge applications, not complex deployments. Benefit from enterprise-grade security, control, and compliance features, including SLAs and SOC2. HUGS Inference supports a diverse range of popular openLLMs, multimodal, and embedding models, including Meta-Llama, Mistral, Qwen, Gemma, and more. Choose between optimized container versions (turbo and light) to balance performance and resource requirements. Deploy pre-configured microservices tailored to your hardware, eliminating manual setup and maximizing efficiency. With HUGS, go from concept to production in minutes, not weeks. Keywords: Generative AI, Inference, Microservices, Open-Source Models, LLMs, Multimodal Models, Embedding Models, Zero-Configuration, Optimized Inference, NVIDIA GPUs, AMD GPUs, Intel GPUs, AWS Inferentia, Habana Gaudi, Google TPUs, OpenAI API, LangChain, LlamaIndex, Kubernetes, Scalability, Security, Compliance, SLA, SOC2, Enterprise-Ready, Hugging Face, Text Generation Inference, Transformers, Meta-Llama, Mistral, Qwen, Gemma.
Anthos
Chooch AI Sustainability provides real-time wildfire detection using Generative AI-powered computer vision in partnership with Google Cloud and Nvidia. Deploy on existing cameras for highly accurate early detection, protecting environmental assets and lives, improving sustainability. Available with fully integrated real-time visual alerts and Smart Analytics with pre-configured reporting. Wildfire Detection Vision AI is offered in the following subscription levels: 1. Chooch Vision AI and Inferencing with Private Cloud Compute provides Detection and Alert Distribution at two pricing tiers: • Up to 50 Cameras • Up to 100 Cameras 2. Chooch Vision AI, Inferencing, and Smart analytics with Private Cloud Compute provides Detection, Alert Distribution, and Alert Visualization at two pricing tiers: • Up to 50 Cameras • Up to 100 Cameras For anything outside the above subscription levels, please contact Chooch sales to receive a custom quote.
Important: For step by step guide on how to setup this vm , please refer to our Getting Started guide Unlock the full power of AI-driven creativity with the Comfy Diffusion VM, a ready-to-deploy virtual machine that brings you Comfy—the most modular and versatile diffusion model interface. Built for artists, developers, and AI enthusiasts, Comfy combines a feature-rich GUI, REST API, and backend framework, all accessible through an intuitive graph-based interface. With Comfy’s node-driven design, users can easily map out complex diffusion processes, experiment with custom pipelines, and create intricate, highly customizable outputs. Ideal for generating unique images, manipulating visual styles, or applying creative effects, this VM is tailored for those who want to leverage cutting-edge diffusion models with minimal setup. Features Powerful Node Graph Interface:Design complex image processing workflows with ease using a drag-and-drop nodes system. Flexibility : Ability to choose any image AI model like Stable Diffusion of your liking or extend the existing models Fully Modular Architecture: Integrate, modify, and customize diffusion models to meet specific project requirements. API Access: Automate workflows or integrate Comfy with other applications via a robust REST API. One-Click Setup: instantly with Comfy pre-installed and pre-configured. Use Cases Creative Content Generation: Ideal for digital artists, graphic designers, and content creators, the Comfy UI VM supports complex, multi-stage image workflows for creating detailed and unique visuals. AI/ML Experimentation: Researchers and developers can leverage the diffusion model interface to test and refine model behaviors, train custom workflows, and experiment with cutting-edge AI techniques. Automated Workflow Integration: Utilize the RESTful API for automated, repeatable image processing tasks, including in web applications or CI/CD pipelines for media-based projects. Educational & Collaborative Use: Perfect for instructors, students, and teams needing a controlled, accessible environment to learn, share, and explore the potential of diffusion-based image synthesis. The Comfy UI Virtual Machine offers a seamless and scalable solution for users looking to explore the full power of Comfy’s capabilities with minimal setup effort. Perfect for those needing a flexible, high-performance environment to push creative and experimental boundaries. Disclaimer: Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and/or names or their products and are the property of their respective owners. We disclaim proprietary interest in the marks and names of others. In order to deploy and use this VM offer, users are required to comply with Stable Diffusion Licensing terms. For more details on the SD licensing terms, please refer to the following link: Stable Diffusion License
Experience up to 10x data pipeline velocity improvements over traditional and cloud-based storage solutions, saving time and money. Application environments that need low-latency access to millions of small files and high bandwidth for large files have limited storage options. The WEKA Data Platform combines dense NVMe storage of Compute Engine instances with Google Cloud Storage in a single, efficient namespace, for your high-performance workloads, scaling to billions of files and hundreds of petabytes. It has a rich feature set that includes transparent object tiering, instantaneous snapshots, snap-to-object (remote clouds), backup, disaster recovery (“DR”), encryption, quotas, Active Directory integration, Kubernetes CSI driver, and much more. The WEKA Data Platform supports multiple file service protocols including full POSIX, NFS, SMB and S3, with full data share-ability across protocols. The WEKA Data Platform delivers the speed, simplicity and scalability for demanding workloads including AI, machine learning, visual effects rendering, genomics, high frequency trading, data analytics, and software builds. WEKA Data Platform Cloud Edition • License for the quantity of an all-flash cluster, built using the NVMe storage on C2-Standard Compute Engine Instances* • POSIX, NFS, SMB, and S3 protocol support • Shared namespace that transparently combines instance-based performance storage with high-capacity Google Cloud Storage to deliver the best overall application performance with the best economics • Snapshot to Google Cloud Storage* provides a low-cost way to protect critical data with fast recovery times for fault tolerance in the event of an availability zone failure • Incremental snapshots that can be scheduled to minute granularity • Snapshots to Google Cloud Storage can enable migration to another cloud region • WEKA Data Platform license can be used for the total quantity of flash storage used across any number of clusters, regardless of cloud region *NOTE: C2-Standard Series Compute Engine instances and Google Cloud Storage cost is not included in the WEKA Data Platform licensing. Pricing is a starting point and is discounted based on total consumption and committed term. Contact orders@weka.io to discuss private contracts and custom prices.
Important : For step by step guide on how to setup this vm , please refer to our Getting Started guide If you are AI/ML practitioner or someone who is starting their AI/ML journey but don’t want to spend hours setting up the right environment , this VM is for you. It includes : 1. Jupyter – Your AI/ML Playground 2. Jupyterhub – Making your AI/ML projects more collaborative by providing multi-user environment and enabling easy code and data sharing 3. Jupyter AI extension - your gateway to generative AI within Jupyter 4. Provides better data privacy and control as your data, models, code & other information is stored on the VM 5. Preinstalled popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn and many more 6. Pre-configured NVIDIA GPU drivers & CUDA libraries The preinstalled Juputer and AI/ML libraries jump-start your AI/ML development by saving you hours of installation time. Jupyterhub gives you the collaboration capabilities by allowing a multi-user environment within the same VM. This not only makes it easy to share the AI/ML work , but makes it more cost efficient in a team setup by allowing multiple users/team members to share the same VM infrastructure instead of each user creating their own VM/notebooks. With the Jupyter AI extension, you can seamlessly integrate with 100+ widely used LLMs from 10+ model providers such as OpenAI for ChatGPT, Anthropic, Hugging Face, AI21, SageMaker to name a few. Complete list of supported LLM Model providers is available here . The Jupyter-AI extension comes with built-in LLM Chat UI for seamless collaboration for generative AI. Enjoy flexibility with support for diverse models and providers, seek code suggestions, debugging tips, or even have code snippets generated for you by interacting with the chat UI. In addition to the Chat UI, the Jupyter-ai extension comes with %ai and %%ai magic commands turning your Jupyter into a generative AI playground anywhere the IPython kernel runs! The VM also has pre-configured NVIDIA GPU drivers & CUDA libraries saving you hours of driver setup and configuration hassle so you can harness the power of GPU resources for your AI/ML workload and conduct advanced data analysis with ease. Watch product preview here For more details please visit Jupyter Python Notebook Support Page.
Note: We provide free demo access for this solution. To request a free demo, please reach out to us at marketing@techlatest.net with the subject "Free Demo Access Request - [Your Company Name]" Ollama is a robust platform designed to simplify the management of large language models (LLMs). It provides a streamlined interface for downloading, running, and fine-tuning models from various vendors. Alongside, the VM is preconfigured with multiple cutting-edge models and allows users to pull and install additional LLMs as needed. The LLMs can be utilized via API integration as well as Open-WebUI based intuitive Chat UI to directly interact with multiple LLMs interactively. This virtual machine comes with GPU support, enabling faster model execution but at a higher cost. If you’re looking for a more cost-effective solution & don’t require GPU acceleration, then please visit our Multi LLM Offer page . What is included in the VM : 1. GPU Support:GPU-boosted LLMs for real-time inference, training, and seamless deployment 2. Preconfigured Models: DeepSeek-R1: with 8B, 14B, 32B, 70B parameters LLaMA 3.3 Mistral Gemma 2 (27B) Qwen 2.5: with 7B, 14B, 32B, 72B parameters Nomic Embed Text 3. Open-WebUI : User-Friendly Interface: Open-WebUI offers an intuitive platform for managing LLMs Centralized Access Control : Support RBAC (Role Based Access Control) to manage access Designed to work seamlessly on both desktop and mobile devices 4. Ollama : Simplified Model Management: Ollama streamlines the process of deploying and interacting with LLMs, making it easier for developers and AI enthusiasts. Integration with Open-WebUI: Offers a cohesive experience by allowing users to manage models directly through the Open-WebUI interface. Key Benefits: Privacy First: Your data remains secure and private, with no risk of 3rd party data exposure No Vendor-Lockin: No need for expensive vendor subscriptions Multipurpose : Whether you're a single user or part of an enterprise team, this VM can be used for AI app development, AI chat alternatives, LLM inference, evaluation & more. GPU Support: Run the LLMs on GPU based instances enabling faster model execution and training Why Choose Techlatest VM Offer? Cost and Time Efficient: Consolidate your models into a single environment, eliminating setup overhead & bandwidth cost of model download Seamless API Integration: Integrate models directly into your applications for custom workflows and automation Effortless Model Management: Simplify model installation and management Disclaimer: Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and/or names or their products and are the property of their respective owners. We disclaim proprietary interest in the marks and names of others. In order to deploy and use this VM offer, users are required to comply with Ollama, Openwebui and preconfigured models licenses and term of agreement listed below. Ollama License Open WebUI License Llama3.3 License DeepSeek-r1 License Qwen2.5 License Mistral License Gemma License Nomic Embed Text License
Important : For step by step guide on how to setup this vm , please refer to our Getting Started guide If you are AI/ML practitioner or someone who is starting their AI/ML journey but don’t want to spend hours setting up the right environment , this VM is for you. It includes : 1. Jupyter – Your AI/ML Playground 2. Jupyterhub – Making your AI/ML projects more collaborative by providing multi-user environment and enabling easy code and data sharing 3. Jupyter AI extension - your gateway to generative AI within Jupyter 4. Provides better data privacy and control as your data, models, code & other information is stored on the VM 5. Preinstalled popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn and many more 6. Pre-configured NVIDIA GPU drivers & CUDA libraries The preinstalled Juputer and AI/ML libraries jump-start your AI/ML development by saving you hours of installation time. Jupyterhub gives you the collaboration capabilities by allowing a multi-user environment within the same VM. This not only makes it easy to share the AI/ML work , but makes it more cost efficient in a team setup by allowing multiple users/team members to share the same VM infrastructure instead of each user creating their own VM/notebooks. With the Jupyter AI extension, you can seamlessly integrate with 100+ widely used LLMs from 10+ model providers such as OpenAI for ChatGPT, Anthropic, Hugging Face, AI21, SageMaker to name a few. Complete list of supported LLM Model providers is available here . The Jupyter-AI extension comes with built-in LLM Chat UI for seamless collaboration for generative AI. Enjoy flexibility with support for diverse models and providers, seek code suggestions, debugging tips, or even have code snippets generated for you by interacting with the chat UI. In addition to the Chat UI, the Jupyter-ai extension comes with %ai and %%ai magic commands turning your Jupyter into a generative AI playground anywhere the IPython kernel runs! The VM also has pre-configured NVIDIA GPU drivers & CUDA libraries saving you hours of driver setup and configuration hassle so you can harness the power of GPU resources for your AI/ML workload and conduct advanced data analysis with ease. Watch product preview here For more details please visit Python AI and ML Kit Page.
ClearVision, powered by ClearObject, is your go-to vision AI processing pipeline tailored for Edge computing, providing you with only the insights you need that provide value to your business. Revolutionize your operations with unparalleled efficiency, cost savings, and enhanced quality control. With ClearVision, real-time analysis and visualization become seamless, empowering you to make informed decisions on the spot. Say goodbye to lag time and hello to instantaneous insights right at the Edge. Why ClearVision? Real-Time Precision: Experience the power of instant analysis with ClearVision, ensuring every decision is based on the most up-to-date data. Cost Efficiency: Cut down on unnecessary expenses by optimizing operations with ClearVision's streamlined Edge computing capabilities. Enhanced Quality Control: Maintain superior quality standards effortlessly by leveraging ClearVision's advanced AI processing. Boosted Throughput: Witness a surge in productivity as ClearVision enables swift data processing, maximizing throughput like never before. Seamless Integration: ClearVision seamlessly integrates into your existing infrastructure, ensuring a smooth transition and minimal disruption to your operations. Transform your manufacturing operations and beyond with ClearVision. Experience the Edge computing revolution firsthand. Get ClearVision today.
Anthos
Cutting-edge AI-driven infrastructure tailored for collecting, analyzing, and interpreting behavioral data. By leveraging the power of AI and machine learning, we transform raw behavioral data into actionable intelligence, enabling organizations to make data-driven decisions with unprecedented accuracy and efficiency. Synerise platform collects unique knowledge about each user from multiple sources and creates a complete 360-degree customer profile, updated in real-time. Automate campaigns and personalize communication via e-mail, SMS, web push and mobile notifications using the intuitive 'drag & drop' editor and ready-to-use templates. Synerise also offers the ability to create various types of analyses, ranging from campaign results, by creating indicators with custom KPIs, to creating your own custom dash boards. Synerise offers usage-based access to the SaaS platform, where organizations can store all heterogeneous data they have - without limits, proceed it in real time and use ready-to-go products enhanced by AI with easy automations to solve daily challenges and speed up growth. Synerise is supporting organizations in (1) collecting & analyzing data about people/customers/users/objects and their environmental context from any data sources in different formats to (2) personalize the experience, predict the future, observe relationships, improve products, generate new revenue streams, optimize costs and execute it (3) at hyper-scale in real-time. Synerise is building a Growth OS with limitless capabilities. Synerise team believes that everyone is (1) unique & wants to feel (2) special in (3) every moment of daily life. That is why Synerise is using AI & Big Data to help companies & organizations to understand people's needs, preferences, and behaviors, avoid fraud & make interactions between them and the brands unique and personalized. Synerise uses (1) the best-in-scale proprietary database created from scratch, (2) state-of-the-art AI algorithms, and (3) powerful automations with practical executive scenarios in one self-service platform, which make it possible. All data is instantly processed in real-time, convenient mode, without tech compromises. Synerise is maximizing the future freedom of its clients by building an API-first intelligence platform with unlimited integration capabilities, a low-code approach, and a unique and open-source proprietary design system, components, libraries, and storybooks. Synerise gives clients an ecosystem to build their apps and ideas without being limited to the company roadmap. We know the joy of winning the development of Synerise in the field of artificial intelligence is confirmed by winning numerous awards (podiums) at international AI competitions alongside such technology giants as Baidu, Nvidiaor Layer6.
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