Alternatives to Darknet
Compare Darknet alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Darknet in 2026. Compare features, ratings, user reviews, pricing, and more from Darknet competitors and alternatives in order to make an informed decision for your business.
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DarkOwl
DarkOwl
We are the industry’s leading provider of darknet data, offering the largest commercially available database of darknet content in the world. DarkOwl offers a suite of data products designed to meet the needs of business looking to quantify risk and understand their threat attack surface by leveraging darknet intelligence. DarkOwl Vision UI and API products make our data easy to access in your browser, native environment or customer-facing platform. Darknet data is a proven driver of business success for use cases spanning beyond threat intelligence and investigations. DarkOwl API products allow cyber insurance underwriters and third party risk assessors to utilize discrete data points from the darknet and incorporate them into scalable business models that accelerate revenue growth. -
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Threat Landscape
Ecliptica Labs AB
Threat Landscape is an automated threat intelligence platform built for security analysts and SOC teams who need high-confidence, actionable intelligence — without the manual triage. The platform continuously ingests and processes global OSINT and darknet sources, automatically extracting structured facts and filtering out noise before it reaches analysts. All intelligence is normalized into STIX 2.1 format, MITRE ATT&CK mapped, and correlated across threat actors, malware families, CVEs, TTPs, and IOCs — so teams spend time acting on intelligence, not building it. Key capabilities include interactive dashboards, visualized STIX threat graphs, advanced search and filtering, darknet monitoring for leak-site claims and criminal chatter, automated daily and weekly digests, and a RESTful API for integration with SIEM, SOAR, and TIP platforms.Starting Price: $499/month -
3
Chainer
Chainer
A powerful, flexible, and intuitive framework for neural networks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug. Comes with ChainerRLA, a library that implements various state-of-the-art deep reinforcement algorithms. Also, with ChainerCVA, a collection of tools to train and run neural networks for computer vision tasks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. -
4
Torch
Torch
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner. -
5
OpenCV
OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.Starting Price: Free -
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SikuliX
SikuliX
SikuliX is an open source automation tool that enables users to automate any visible element on their desktop screens across Windows, Mac, or certain Linux/Unix systems. It utilizes image recognition powered by OpenCV to identify and interact with screen elements, allowing for the automation of tasks that are otherwise difficult to script. SikuliX offers an Integrated Development Environment (IDE) for writing visual scripts using screenshots, as well as a Java API for integrating image-based automation into existing applications. The software packages representing SikuliX are open source under the MIT license and publicly available for whatever use. SikuliX internally uses OpenCV to support image-related features and Tesseract for text features. The latest stable version, SikuliX 1.1.1, is recommended for use.Starting Price: Free -
7
Social Links
Social Links
We bring together data from 500+ open sources covering social media, messengers, blockchains, and the dark web, to visualize and analyze a holistic picture for streamlining investigations. Conduct investigations across 500+ open sources with the help of 1700+ search methods. Extract user profiles, numbers, messages, groups, and more. View transactions, addresses, senders, recipients, and more. Access an expansive set of original search methods. Gain full access to darknet marketplaces, forums, and more. Delve into an extensive set of corporate sources. A suite of data extraction and analysis methods across social media, blockchains, messengers, and the dark web is connected directly to your in-house platform via our API. An enterprise-grade on-premise OSINT platform with customization options, private data storage, and our widest range of search methods. Companies from S&P500 and law enforcement agencies from 80+ countries rely on Social Links' solutions. -
8
HTTPCS Cyber Vigilance
Ziwit
HTTPCS solutions comparison vs the other automated tools on the cybersecurity market. The features of each HTTPCS solution have been compared to the features of alternative solutions available on the cybersecurity market. Click on a tab and discover HTTPCS, a complete alternative to other cybersecurity solutions. 4 tools have been compared to HTTPCS Cyber Vigilance, a darknet monitoring tool that warns you in real-time if your organization becomes the target of a cyberattack. 6 tools to scan and detect security breaches on websites have been compared to HTTPCS Security, the vulnerability scanner with a 0 false-positive guarantee. 4 web integrity monitoring products and viewing of changes have been compared to HTTPCS Integrity, a cybersecurity solution which detects malicious files, malware and internal errors. Request a demo or try a free 14-day trial for HTTPCS Integrity and see for yourself its features! -
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LifeRaft Navigator
Navigator
Consolidate, assess, and investigate intelligence in a single platform. Collect and alert on data relevant to your security operations from social media, deep web, and darknet sources 24/7. Our unified intelligence platform automates collection and filtering, and provides a suite of investigative tools to explore and validate threats. Uncover critical information that impacts the security of your assets and operations. Navigator monitors the internet 24/7 with custom search criteria to detect high-risk threats to your people, assets, and operations from diversified sources. Finding the needle in the haystack is a growing challenge for security operations teams. Navigator provides advanced filtering tools to capture the breadth of the online threat landscape. Uncover, explore, and use a variety of sources to validate intelligence related to threat actors, events, and special interest projects or security issues. -
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OpenFaceTracker
OpenFaceTracker
OpenFaceTracker is a facial recognition program capable to detect one or several faces on a picture or a video, and to identify them via a database. OpenFaceTracker needs OpenCV3.2 and QT4 installed on your machine, you’ve got two options, if you love compiling libraries by hand, please follow build_oft, and installing Opencv and QT using your favorite packaging tool. You can compile OFT as a library or you can compile it as a standalone binary file. You can then open the file and execute the detection and recognition module. You can show help and exit, show the list of all available cameras, you can test the XML DB, read from the OFT config, and check the environment. OpenFaceTrackerLib uses Opencv 3.2. This latter has introduced many new algorithms and features comparing to version 2.4. Some modules have been rewritten, some have been reorganized. Although most of the algorithms from 2.4 are still present, the interfaces can differ. -
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Microsoft Cognitive Toolkit
Microsoft
The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub. -
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DeepPy
DeepPy
DeepPy is a MIT licensed deep learning framework. DeepPy tries to add a touch of zen to deep learning as it. DeepPy relies on CUDArray for most of its calculations. Therefore, you must first install CUDArray. Note that you can choose to install CUDArray without the CUDA back-end which simplifies the installation process. -
13
Deeplearning4j
Deeplearning4j
DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers. -
14
CUDA
NVIDIA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.Starting Price: Free -
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FonePaw Video Converter Ultimate
FonePaw
Multifunctional software makes it possible for you to convert, edit and play videos, DVD and audios. In addition, you can also create you own videos or GIF image freely with it. You can convert one video at a time or add several video files for converting simultaneously. It can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. Your video will not be quality loss. Equipped with NVIDIA's CUDA and AMD APP acceleration technology, you're able to experience 6X faster conversion speed and supports multi-core processor completely. Supported with NVIDIA® CUDA™, AMD®, etc. technologies, FonePaw Video Converter Ultimate can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. This all-in-one video converter is capable of converting video, audio and DVD files efficiently and even editing them with better effect.Starting Price: $39 one-time payment -
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SimpleCV
SimpleCV
SimpleCV is an open-source framework for building computer vision applications. With it, you get access to several high-powered computer vision libraries such as OpenCV, without having to first learn about bit depths, file formats, color spaces, buffer management, eigenvalues, or matrix versus bitmap storage. This is computer vision made easy. These are just a small number of things you can do with SimpleCV. If you would like to learn more please refer to our tutorial. There are also many examples included in the SimpleCV directory under the examples folder which can also be downloaded from here. SimpleCV is an open-source framework, meaning that it is a collection of libraries and software that you can use to develop vision applications. It lets you work with the images or video streams that come from webcams, Kinects, FireWire and IP cameras, or mobile phones. It helps you build software to make your various technologies not only see the world but understand it too. -
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NVIDIA DRIVE
NVIDIA
Software is what turns a vehicle into an intelligent machine. The NVIDIA DRIVE™ Software stack is open, empowering developers to efficiently build and deploy a variety of state-of-the-art AV applications, including perception, localization and mapping, planning and control, driver monitoring, and natural language processing. The foundation of the DRIVE Software stack, DRIVE OS is the first safe operating system for accelerated computing. It includes NvMedia for sensor input processing, NVIDIA CUDA® libraries for efficient parallel computing implementations, NVIDIA TensorRT™ for real-time AI inference, and other developer tools and modules to access hardware engines. The NVIDIA DriveWorks® SDK provides middleware functions on top of DRIVE OS that are fundamental to autonomous vehicle development. These consist of the sensor abstraction layer (SAL) and sensor plugins, data recorder, vehicle I/O support, and a deep neural network (DNN) framework. -
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NVIDIA Isaac
NVIDIA
NVIDIA Isaac is an AI robot development platform that comprises NVIDIA CUDA-accelerated libraries, application frameworks, and AI models to expedite the creation of AI robots, including autonomous mobile robots, robotic arms, and humanoids. The platform features NVIDIA Isaac ROS, a collection of CUDA-accelerated computing packages and AI models built on the open source ROS 2 framework, designed to streamline the development of advanced AI robotics applications. Isaac Manipulator, built on Isaac ROS, enables the development of AI-powered robotic arms that can seamlessly perceive, understand, and interact with their environments. Isaac Perceptor facilitates the rapid development of advanced AMRs capable of operating in unstructured environments like warehouses or factories. For humanoid robotics, NVIDIA Isaac GR00T serves as a research initiative and development platform for general-purpose robot foundation models and data pipelines. -
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YandexART
Yandex
YandexART is a diffusion neural network by Yandex designed for image and video creation. This new neural network ranks as a global leader among generative models in terms of image generation quality. Integrated into Yandex services like Yandex Business and Shedevrum, it generates images and videos using the cascade diffusion method—initially creating images based on requests and progressively enhancing their resolution while infusing them with intricate details. The updated version of this neural network is already operational within the Shedevrum application, enhancing user experiences. YandexART fueling Shedevrum boasts an immense scale, with 5 billion parameters, and underwent training on an extensive dataset comprising 330 million pairs of images and corresponding text descriptions. Through the fusion of a refined dataset, a proprietary text encoder, and reinforcement learning, Shedevrum consistently delivers high-calibre content. -
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Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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21
AForge.NET
AForge.NET
AForge.NET is an open source C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, fuzzy logic, machine learning, robotics, etc. The work on the framework's improvement is in constants progress, what means that new feature and namespaces are coming constantly. To get knowledge about its progress you may track source repository's log or visit project discussion group to get the latest information about it. The framework is provided not only with different libraries and their sources, but with many sample applications, which demonstrate the use of this framework, and with documentation help files, which are provided in HTML Help format. -
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NVIDIA DIGITS
NVIDIA DIGITS
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. Interactively train models using TensorFlow and visualize model architecture using TensorBoard. Integrate custom plug-ins for importing special data formats such as DICOM used in medical imaging. -
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Hololink
Hololink
Hololink is a powerful, web-based platform that empowers creators to build and share immersive augmented reality (AR) experiences—no coding required. Designed for accessibility and impact, Hololink’s intuitive drag-and-drop editor enables anyone to craft interactive, media-rich AR experiences directly in the browser, with no need for downloads or installations. Key Features: No App Needed: Launch AR directly in mobile browsers for easy, instant access. Advanced Tracking • Image Tracking: Single and multi-image tracking using Hololink’s custom OpenCV engine. • Surface & World: Place AR on flat surfaces or in space with WebAR. • 360° Content: Supports 360° images and video for immersive scenes. Rich Media Add 3D models, images, video, audio, and text for engaging, layered content. Interactive Actions Tap to trigger animations and play media making scenes interactive and alive. Visual Storyboard See and edit the entire user-flow in our visual storyboard.Starting Price: €9/month -
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Unicorn Render
Unicorn Render
Unicorn Render is a professional rendering software that enables users to produce stunning realistic pictures and achieve high-end rendering levels without any prior skills. It offers a user-friendly interface designed to provide everything needed to obtain amazing results with minimal controls. Available as a standalone application or as a plugin, Unicorn Render integrates advanced AI technology and professional visualization tools. The software supports GPU+CPU acceleration through deep learning photorealistic rendering technology and NVIDIA CUDA technology, allowing joint support for CUDA GPUs and multicore CPUs. It features real-time progressive physics illumination, a Metropolis Light Transport sampler (MLT), a caustic sampler, and native NVIDIA MDL material support. Unicorn Render's WYSIWYG editing mode ensures that 100% of editing can be done in final image quality, eliminating surprises in the production of the final image. -
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NVIDIA TensorRT
NVIDIA
NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.Starting Price: Free -
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Supervisely
Supervisely
The leading platform for entire computer vision lifecycle. Iterate from image annotation to accurate neural networks 10x faster. With our best-in-class data labeling tools transform your images / videos / 3d point cloud into high-quality training data. Train your models, track experiments, visualize and continuously improve model predictions, build custom solution within the single environment. Our self-hosted solution guaranties data privacy, powerful customization capabilities, and easy integration into your technology stack. A turnkey solution for Computer Vision: multi-format data annotation & management, quality control at scale and neural networks training in end-to-end platform. Inspired by professional video editing software, created by data scientists for data scientists — the most powerful video labeling tool for machine learning and more. -
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ccminer
ccminer
ccminer is an open-source project for CUDA compatible GPUs (nVidia). The project is compatible with both Linux and Windows platforms. This site is intended to share cryptocurrencies mining tools you can trust. Available open-source binaries will be compiled and signed by us. Most of these projects are open-source but could require technical abilities to be compiled correctly. -
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RocketWhisper
Mojosoft Co., Ltd.
RocketWhisper is a powerful desktop speech recognition and transcription application that runs 100% offline on your computer. Your voice data never leaves your machine - complete privacy guaranteed. Powered by OpenAI's Whisper engine with NVIDIA GPU (CUDA) acceleration, RocketWhisper delivers fast and accurate speech-to-text conversion for professionals, content creators, and anyone who works with voice and text. Key Features: - 100% offline processing - voice data never leaves your PC - OpenAI Whisper engine for high-accuracy speech recognition - NVIDIA CUDA GPU acceleration - up to 10x faster than CPU - Real-time voice-to-text input with global hotkey (Push-to-Talk with Right Alt) - Batch transcription of multiple audio/video files (MP3, WAV, M4A, MP4, MKV, AVI, etc.) - SRT/VTT subtitle export for video content - AI text formatting with LLM integration (OpenAI, Anthropic, Google Gemini, Grok, local LLM)Starting Price: $32 one-time -
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Weasis
Weasis
Weasis is a free, open source DICOM viewer designed for both standalone and web-based use, featuring a highly modular architecture. It is widely utilized in healthcare settings, including hospitals, health networks, multicenter research trials, and by patients. As cross-platform software, Weasis offers flexible integration with PACS, RIS, HIS, or EHR systems. The viewer leverages the OpenCV library to deliver high-performance and high-quality medical imaging renderings. From version 4 onwards, Weasis features a responsive user interface aligned with operating system options, offering an enhanced experience on high-resolution screens. Key features include support for a wide range of DICOM files, such as multi-frame, enhanced, MPEG-2, MPEG-4, and more. Users can import DICOM files via DICOM Query/Retrieve (C-GET, C-MOVE, and WADO-URI) and DICOMWeb (QUERY and RETRIEVE), as well as import and export DICOM CD/DVD with DICOMDIR.Starting Price: Free -
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Zebra by Mipsology
Mipsology
Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application. Zebra computes neural networks at world-class speed, setting a new standard for performance. Zebra runs on highest-throughput boards all the way to the smallest boards. The scaling provides the required throughput, in data centers, at the edge, or in the cloud. Zebra accelerates any neural network, including user-defined neural networks. Zebra processes the same CPU/GPU-based trained neural network with the same accuracy without any change. -
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ThirdAI
ThirdAI
ThirdAI (pronunciation: /THərd ī/ Third eye) is a cutting-edge Artificial intelligence startup carving scalable and sustainable AI. ThirdAI accelerator builds hash-based processing algorithms for training and inference with neural networks. The technology is a result of 10 years of innovation in finding efficient (beyond tensor) mathematics for deep learning. Our algorithmic innovation has demonstrated how we can make Commodity x86 CPUs 15x or faster than most potent NVIDIA GPUs for training large neural networks. The demonstration has shaken the common knowledge prevailing in the AI community that specialized processors like GPUs are significantly superior to CPUs for training neural networks. Our innovation would not only benefit current AI training by shifting to lower-cost CPUs, but it should also allow the “unlocking” of AI training workloads on GPUs that were not previously feasible. -
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GPUonCLOUD
GPUonCLOUD
Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.Starting Price: $1 per hour -
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Bokeh
Bokeh
Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.Starting Price: Free -
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ConvNetJS
ConvNetJS
ConvNetJS is a Javascript library for training deep learning models (neural networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. The library allows you to formulate and solve neural networks in Javascript, and was originally written by @karpathy. However, the library has since been extended by contributions from the community and more are warmly welcome. The fastest way to obtain the library in a plug-and-play way if you don't care about developing is through this link to convnet-min.js, which contains the minified library. Alternatively, you can also choose to download the latest release of the library from Github. The file you are probably most interested in is build/convnet-min.js, which contains the entire library. To use it, create a bare-bones index.html file in some folder and copy build/convnet-min.js to the same folder. -
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SHARK
SHARK
SHARK is a fast, modular, feature-rich open-source C++ machine learning library. It provides methods for linear and nonlinear optimization, kernel-based learning algorithms, neural networks, and various other machine learning techniques. It serves as a powerful toolbox for real-world applications as well as research. Shark depends on Boost and CMake. It is compatible with Windows, Solaris, MacOS X, and Linux. Shark is licensed under the permissive GNU Lesser General Public License. Shark provides an excellent trade-off between flexibility and ease-of-use on the one hand, and computational efficiency on the other. Shark offers numerous algorithms from various machine learning and computational intelligence domains in a way that they can be easily combined and extended. Shark comes with a lot of powerful algorithms that are to our best knowledge not implemented in any other library. -
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NeuroIntelligence
ALYUDA
NeuroIntelligence is a neural networks software application designed to assist neural network, data mining, pattern recognition, and predictive modeling experts in solving real-world problems. NeuroIntelligence features only proven neural network modeling algorithms and neural net techniques; software is fast and easy-to-use. Visualized architecture search, neural network training and testing. Neural network architecture search, fitness bars, network training graphs comparison. Training graphs, dataset error, network error, weights and errors distribution, neural network input importance. Testing, actual vs. output graph, scatter plot, response graph, ROC curve, confusion matrix. The interface of NeuroIntelligence is optimized to solve data mining, forecasting, classification and pattern recognition problems. You can create a better solution much faster using the tool's easy-to-use GUI and unique time-saving capabilities.Starting Price: $497 per user -
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Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
38
PotPlayer
Potplayer
Provides the maximum performance with the minumum resource using DXVA, CUDA, QuickSync. Supports various types of 3D glasses so you can get the 3D experience anytime you want using your 3DTV or PC. Various output format. No need to install different codecs all the time when using the player. Supports OpenCodec so users can easily add whatever codecs they want. You can bookmark your favorite scene or chapter. Choose which one when you have 2 sound cards. We support Direct3D9 Ex Flip Mode and Overlay.Starting Price: Free -
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qikkDB
qikkDB
QikkDB is a GPU accelerated columnar database, delivering stellar performance for complex polygon operations and big data analytics. When you count your data in billions and want to see real-time results you need qikkDB. We support Windows and Linux operating systems. We use Google Tests as the testing framework. There are hundreds of unit tests and tens of integration tests in the project. For development on Windows, Microsoft Visual Studio 2019 is recommended, and its dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, vcpkg, boost. For development on Linux, the dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, and boost. This project is licensed under the Apache License, Version 2.0. You can use an installation script or dockerfile to install qikkDB. -
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NVIDIA Brev
NVIDIA
NVIDIA Brev is a cloud-based platform that provides instant access to fully configured GPU environments optimized for AI and machine learning development. Its Launchables feature offers prebuilt, customizable compute setups that let developers start projects quickly without complex setup or configuration. Users can create Launchables by specifying GPU resources, Docker images, and project files, then share them easily with collaborators. The platform also offers prebuilt Launchables featuring the latest AI frameworks, microservices, and NVIDIA Blueprints to jumpstart development. NVIDIA Brev provides a seamless GPU sandbox with support for CUDA, Python, and Jupyter Lab accessible via browser or CLI. This enables developers to fine-tune, train, and deploy AI models with minimal friction and maximum flexibility.Starting Price: $0.04 per hour -
41
Fido
Fido
Fido is a light-weight, open-source, and highly modular C++ machine learning library. The library is targeted towards embedded electronics and robotics. Fido includes implementations of trainable neural networks, reinforcement learning methods, genetic algorithms, and a full-fledged robotic simulator. Fido also comes packaged with a human-trainable robot control system as described in Truell and Gruenstein. While the simulator is not in the most recent release, it can be found for experimentation on the simulator branch. -
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NVIDIA GPU-Optimized AMI
Amazon
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This AMI 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 AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'Starting Price: $3.06 per hour -
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Sharky Neural Network
SharkTime Software
Sharky Neural Network is a Windows application providing a visual, interactive introduction to machine learning. This free software serves as a playground for experimenting with neural network classification in real-time. Instead of relying on static charts, Sharky offers a "live view" of the learning process. You can watch the network adjust its classification boundaries like a movie unfolding on your screen. Users can swap architectures and data shapes to see how topology affects results. The app uses the backpropagation algorithm with optional momentum to give you direct control over learning dynamics. Perfect for students and hobbyists, Sharky Neural Network makes hidden layers and data clustering intuitive. It is a lightweight tool that effectively bridges the gap between theory and practice.Starting Price: $0 -
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NVIDIA Magnum IO
NVIDIA
NVIDIA Magnum IO is the architecture for parallel, intelligent data center I/O. It maximizes storage, network, and multi-node, multi-GPU communications for the world’s most important applications, using large language models, recommender systems, imaging, simulation, and scientific research. Magnum IO utilizes storage I/O, network I/O, in-network compute, and I/O management to simplify and speed up data movement, access, and management for multi-GPU, multi-node systems. It supports NVIDIA CUDA-X libraries and makes the best use of a range of NVIDIA GPU and networking hardware topologies to achieve optimal throughput and low latency. In multi-GPU, multi-node systems, slow CPU, single-thread performance is in the critical path of data access from local or remote storage devices. With storage I/O acceleration, the GPU bypasses the CPU and system memory, and accesses remote storage via 8x 200 Gb/s NICs, achieving up to 1.6 TB/s of raw storage bandwidth. -
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NVIDIA Modulus
NVIDIA
NVIDIA Modulus is a neural network framework that blends the power of physics in the form of governing partial differential equations (PDEs) with data to build high-fidelity, parameterized surrogate models with near-real-time latency. Whether you’re looking to get started with AI-driven physics problems or designing digital twin models for complex non-linear, multi-physics systems, NVIDIA Modulus can support your work. Offers building blocks for developing physics machine learning surrogate models that combine both physics and data. The framework is generalizable to different domains and use cases—from engineering simulations to life sciences and from forward simulations to inverse/data assimilation problems. Provides parameterized system representation that solves for multiple scenarios in near real time, letting you train once offline to infer in real time repeatedly. -
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Neural Designer
Artelnics
Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.Starting Price: $2495/year (per user) -
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TFLearn
TFLearn
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorial and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations and more. The high-level API currently supports most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, Generative networks. -
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RightNow AI
RightNow AI
RightNow AI is an AI-powered platform designed to automatically profile, detect bottlenecks, and optimize CUDA kernels for peak performance. It supports all major NVIDIA architectures, including Ampere, Hopper, Ada Lovelace, and Blackwell GPUs. It enables users to generate optimized CUDA kernels instantly using natural language prompts, eliminating the need for deep GPU expertise. With serverless GPU profiling, users can identify performance issues without relying on local hardware. RightNow AI replaces complex legacy optimization tools with a streamlined solution, offering features such as inference-time scaling and performance benchmarking. Trusted by leading AI and HPC teams worldwide, including Nvidia, Adobe, and Samsung, RightNow AI has demonstrated performance improvements ranging from 2x to 20x over standard implementations.Starting Price: $20 per month -
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Cogniac
Cogniac
Cogniac’s no-code solution enables organizations to capitalize on the latest developments in Artificial Intelligence (AI) and convolutional neural networks to deliver superhuman operational performance. Cogniac’s AI machine vision platform enables enterprise customers to achieve Industry 4.0 standards through visual data management and automation. Cogniac helps organizations’ operations divisions deliver smart continuous improvement. The Cogniac user interface has been designed and built to be operated by a non-technical user. With simplicity at its heart, the drag and drop nature of the Cogniac platform allows subject matter experts to focus on the tasks that drive the most value. Cogniac’s platform can identify defects from as little as 100 labeled images. Once trained by 25 approved and 75 defective images, the Cogniac AI will deliver results that are comparable to a human subject matter expert within hours of set-up. -
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Latent AI
Latent AI
We take the hard work out of AI processing on the edge. The Latent AI Efficient Inference Platform (LEIP) enables adaptive AI at the edge by optimizing for compute, energy and memory without requiring changes to existing AI/ML infrastructure and frameworks. LEIP is a modular, fully-integrated workflow designed to train, quantize, adapt and deploy edge AI neural networks. LEIP is a modular, fully-integrated workflow designed to train, quantize and deploy edge AI neural networks. Latent AI believes in a vibrant and sustainable future driven by the power of AI and the promise of edge computing. Our mission is to deliver on the vast potential of edge AI with solutions that are efficient, practical, and useful. Latent AI helps a variety of federal and commercial organizations gain the most from their edge AI with an automated edge MLOps pipeline that creates ultra-efficient, compressed, and secured edge models at scale while also removing all maintenance and configuration concerns
