Alternatives to TensorBlock
Compare TensorBlock alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to TensorBlock in 2026. Compare features, ratings, user reviews, pricing, and more from TensorBlock competitors and alternatives in order to make an informed decision for your business.
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1
Cloudflare
Cloudflare
Cloudflare is the foundation for your infrastructure, applications, and teams. Cloudflare secures and ensures the reliability of your external-facing resources such as websites, APIs, and applications. It protects your internal resources such as behind-the-firewall applications, teams, and devices. And it is your platform for developing globally scalable applications. Your website, APIs, and applications are your key channels for doing business with your customers and suppliers. As more and more shift online, ensuring these resources are secure, performant and reliable is a business imperative. Cloudflare for Infrastructure is a complete solution to enable this for anything connected to the Internet. Behind-the-firewall applications and devices are foundational to the work of your internal teams. The recent surge in remote work is testing the limits of many organizations’ VPN and other hardware solutions. -
2
Vercel
Vercel
Vercel is an AI-powered cloud platform that helps developers build, deploy, and scale high-performance web experiences with speed and security. It provides a unified set of tools, templates, and infrastructure designed to streamline development workflows from idea to global deployment. With support for modern frameworks like Next.js, Svelte, Vite, and Nuxt, teams can ship fast, responsive applications without managing complex backend operations. Vercel’s AI Cloud includes an AI Gateway, SDKs, workflow automation tools, and fluid compute, enabling developers to integrate large language models and advanced AI features effortlessly. The platform emphasizes instant global distribution, enabling deployments to become available worldwide immediately after a git push. Backed by strong security and performance optimizations, Vercel helps companies deliver personalized, reliable digital experiences at massive scale. -
3
BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
4
TensorFlow
TensorFlow
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.Starting Price: Free -
5
Abliteration.ai
Abliteration.ai
Abliteration.ai is a developer-focused AI platform that provides access to unrestricted large language models combined with a policy control layer, allowing teams to define exactly how models should behave rather than relying on built-in provider restrictions. It offers an OpenAI-compatible API, enabling seamless integration into existing tools, SDKs, and workflows without requiring major changes to infrastructure. Abliteration.ai’s core concept is “unrestricted, not ungoverned,” meaning developers can use less-censored models while enforcing their own rules through a Policy Gateway that applies real-time controls such as allowing, blocking, redacting, or escalating outputs based on custom policies. These policies are written as code and can be audited, simulated, and deployed with features like shadow testing and rollback safeguards. Abliteration.ai supports advanced use cases such as security testing, red teaming, synthetic data generation, and specialized research workflows.Starting Price: $20 per month -
6
Portkey
Portkey.ai
Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!Starting Price: $49 per month -
7
Orq.ai
Orq.ai
Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security. -
8
Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
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Azure Machine Learning
Microsoft
Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. -
10
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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Edgee
Edgee
Edgee is an AI gateway that sits between your application and large language model providers, acting as an edge intelligence layer that compresses prompts before they reach the model to reduce token usage, lower costs, and improve latency without changing your existing code. Applications call Edgee through a single OpenAI-compatible API, and Edgee applies edge-level policies such as intelligent token compression, routing, privacy controls, retries, caching, and cost governance before forwarding requests to the selected provider, including OpenAI, Anthropic, Gemini, xAI, and Mistral. Its token compression engine removes redundant input tokens while preserving semantic intent and context, achieving up to 50% input token reduction, which is especially valuable for long contexts, RAG pipelines, and multi-turn agents. Edgee enables tagging requests with custom metadata to track usage and spending by feature, team, project, or environment, and provides cost alerts when spending spikes.Starting Price: Free -
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LLM Gateway
LLM Gateway
LLM Gateway is a fully open source, unified API gateway that lets you route, manage, and analyze requests to any large language model provider, OpenAI, Anthropic, Gemini Enterprise Agent Platform, and more, using a single, OpenAI-compatible endpoint. It offers multi-provider support with seamless migration and integration, dynamic model orchestration that routes each request to the optimal engine, and comprehensive usage analytics to track requests, token consumption, response times, and costs in real time. Built-in performance monitoring lets you compare models’ accuracy and cost-effectiveness, while secure key management centralizes API credentials under role-based controls. You can deploy LLM Gateway on your own infrastructure under the MIT license or use the hosted service as a progressive web app, and simple integration means you only need to change your API base URL, your existing code in any language or framework (cURL, Python, TypeScript, Go, etc.)Starting Price: $50 per month -
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Luminal
Luminal
Luminal is a machine-learning framework built for speed, simplicity, and composability, focusing on static graphs and compiler-based optimization to deliver high performance even for complex neural networks. It compiles models into minimal “primops” (only 12 primitive operations) and then applies compiler passes to replace those with device-specific optimized kernels, enabling efficient execution on GPU or other backends. It supports modules (building blocks of networks with a standard forward API) and the GraphTensor interface (typed tensors and graphs at compile time) for model definition and execution. Luminal’s core remains intentionally small and hackable, with extensibility via external compilers for datatypes, devices, training, quantization, and more. Quick-start guidance shows how to clone the repo, build a “Hello World” example, or run a larger model like LLaMA 3 using GPU features. -
14
TensorBoard
Tensorflow
TensorBoard is TensorFlow's comprehensive visualization toolkit designed to facilitate machine learning experimentation. It enables users to track and visualize metrics such as loss and accuracy, visualize the model graph (operations and layers), view histograms of weights, biases, or other tensors as they change over time, project embeddings to a lower-dimensional space, and display images, text, and audio data. Additionally, TensorBoard offers profiling capabilities to optimize TensorFlow programs. These features collectively provide a suite of tools to understand, debug, and optimize TensorFlow programs, enhancing the machine learning workflow. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics, visualizing the model graph, and projecting embeddings to a lower dimensional space.Starting Price: Free -
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Crazyrouter
Crazyrouter
Crazyrouter is an AI API gateway that gives developers access to 300+ AI models through a single API key. Compatible with the OpenAI SDK format, it supports GPT-5, Claude, Gemini, DeepSeek, Llama, Mistral, and hundreds more — all at prices up to 50% lower than going direct to providers Key Features: • One API key for 300+ models (OpenAI, Anthropic, Google, Meta, etc.) • OpenAI-compatible API format — zero code changes to switch • Pay-as-you-go pricing with no monthly subscriptions • Built-in load balancing, failover, and rate limit management • Real-time usage dashboard and token tracking • Support for text, image, video, audio, and embedding models • Enterprise-grade uptime with multi-region infrastructure Ideal for developers, startups, and teams who want to experiment with multiple AI models without managing separate API keys and billing accounts.Starting Price: Free -
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Google AI Edge
Google
Google AI Edge offers a comprehensive suite of tools and frameworks designed to facilitate the deployment of artificial intelligence across mobile, web, and embedded applications. By enabling on-device processing, it reduces latency, allows offline functionality, and ensures data remains local and private. It supports cross-platform compatibility, allowing the same model to run seamlessly across embedded systems. It is also multi-framework compatible, working with models from JAX, Keras, PyTorch, and TensorFlow. Key components include low-code APIs for common AI tasks through MediaPipe, enabling quick integration of generative AI, vision, text, and audio functionalities. Visualize the transformation of your model through conversion and quantification. Overlays the results of the comparisons to debug the hotspots. Explore, debug, and compare your models visually. Overlays comparisons and numerical performance data to identify problematic hotspots.Starting Price: Free -
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FastRouter
FastRouter
FastRouter is a unified API gateway that enables AI applications to access many large language, image, and audio models (like GPT-5, Claude 4 Opus, Gemini 2.5 Pro, Grok 4, etc.) through a single OpenAI-compatible endpoint. It features automatic routing, which dynamically picks the optimal model per request based on factors like cost, latency, and output quality. It supports massive scale (no imposed QPS limits) and ensures high availability via instant failover across model providers. FastRouter also includes cost control and governance tools to set budgets, rate limits, and model permissions per API key or project, and it delivers real-time analytics on token usage, request counts, and spending trends. The integration process is minimal; you simply swap your OpenAI base URL to FastRouter’s endpoint and configure preferences in the dashboard; the routing, optimization, and failover functions then run transparently. -
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NVIDIA FLARE
NVIDIA
NVIDIA FLARE (Federated Learning Application Runtime Environment) is an open source, extensible SDK designed to facilitate federated learning across diverse industries, including healthcare, finance, and automotive. It enables secure, privacy-preserving AI model training by allowing multiple parties to collaboratively train models without sharing raw data. FLARE supports various machine learning frameworks such as PyTorch, TensorFlow, RAPIDS, and XGBoost, making it adaptable to existing workflows. FLARE's componentized architecture allows for customization and scalability, supporting both horizontal and vertical federated learning. It is suitable for applications requiring data privacy and regulatory compliance, such as medical imaging and financial analytics. It is available for download via the NVIDIA NVFlare GitHub repository and PyPi.Starting Price: Free -
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TensorWave
TensorWave
TensorWave is an AI and high-performance computing (HPC) cloud platform purpose-built for performance, powered exclusively by AMD Instinct Series GPUs. It delivers high-bandwidth, memory-optimized infrastructure that scales with your most demanding models, training, or inference. TensorWave offers access to AMD’s top-tier GPUs within seconds, including the MI300X and MI325X accelerators, which feature industry-leading memory capacity and bandwidth, with up to 256GB of HBM3E supporting 6.0TB/s. TensorWave's architecture includes UEC-ready capabilities that optimize the next generation of Ethernet for AI and HPC networking, and direct liquid cooling that delivers exceptional total cost of ownership with up to 51% data center energy cost savings. TensorWave provides high-speed network storage, ensuring game-changing performance, security, and scalability for AI pipelines. It offers plug-and-play compatibility with a wide range of tools and platforms, supporting models, libraries, etc. -
20
LM Studio
LM Studio
Use models through the in-app Chat UI or an OpenAI-compatible local server. Minimum requirements: M1/M2/M3 Mac, or a Windows PC with a processor that supports AVX2. Linux is available in beta. One of the main reasons for using a local LLM is privacy, and LM Studio is designed for that. Your data remains private and local to your machine. You can use LLMs you load within LM Studio via an API server running on localhost. -
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DagsHub
DagsHub
DagsHub is a collaborative platform designed for data scientists and machine learning engineers to manage and streamline their projects. It integrates code, data, experiments, and models into a unified environment, facilitating efficient project management and team collaboration. Key features include dataset management, experiment tracking, model registry, and data and model lineage, all accessible through a user-friendly interface. DagsHub supports seamless integration with popular MLOps tools, allowing users to leverage their existing workflows. By providing a centralized hub for all project components, DagsHub enhances transparency, reproducibility, and efficiency in machine learning development. DagsHub is a platform for AI and ML developers that lets you manage and collaborate on your data, models, and experiments, alongside your code. DagsHub was particularly designed for unstructured data for example text, images, audio, medical imaging, and binary files.Starting Price: $9 per month -
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NVIDIA Triton™ inference server delivers fast and scalable AI in production. Open-source inference serving software, Triton inference server streamlines AI inference by enabling teams deploy trained AI models from any framework (TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, custom and more on any GPU- or CPU-based infrastructure (cloud, data center, or edge). Triton runs models concurrently on GPUs to maximize throughput and utilization, supports x86 and ARM CPU-based inferencing, and offers features like dynamic batching, model analyzer, model ensemble, and audio streaming. Triton helps developers deliver high-performance inference aTriton integrates with Kubernetes for orchestration and scaling, exports Prometheus metrics for monitoring, supports live model updates, and can be used in all major public cloud machine learning (ML) and managed Kubernetes platforms. Triton helps standardize model deployment in production.Starting Price: Free
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APIPark
APIPark
APIPark is an open-source, all-in-one AI gateway and API developer portal, that helps developers and enterprises easily manage, integrate, and deploy AI services. No matter which AI model you use, APIPark provides a one-stop integration solution. It unifies the management of all authentication information and tracks the costs of API calls. Standardize the request data format for all AI models. When switching AI models or modifying prompts, it won’t affect your app or microservices, simplifying your AI usage and reducing maintenance costs. You can quickly combine AI models and prompts into new APIs. For example, using OpenAI GPT-4 and custom prompts, you can create sentiment analysis APIs, translation APIs, or data analysis APIs. API lifecycle management helps standardize the process of managing APIs, including traffic forwarding, load balancing, and managing different versions of publicly accessible APIs. This improves API quality and maintainability.Starting Price: Free -
24
RankLLM
Castorini
RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs.Starting Price: Free -
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Kong AI Gateway
Kong Inc.
Kong AI Gateway is a semantic AI gateway designed to run and secure Large Language Model (LLM) traffic, enabling faster adoption of Generative AI (GenAI) through new semantic AI plugins for Kong Gateway. It allows users to easily integrate, secure, and monitor popular LLMs. The gateway enhances AI requests with semantic caching and security features, introducing advanced prompt engineering for compliance and governance. Developers can power existing AI applications written using SDKs or AI frameworks by simply changing one line of code, simplifying migration. Kong AI Gateway also offers no-code AI integrations, allowing users to transform, enrich, and augment API responses without writing code, using declarative configuration. It implements advanced prompt security by determining allowed behaviors and enables the creation of better prompts with AI templates compatible with the OpenAI interface. -
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luminoth
luminoth
Luminoth is an open source toolkit for computer vision. Currently, we support object detection, but we are aiming for much more. : Luminoth is still alpha-quality release, which means the internal and external interfaces (such as command line) are very likely to change as the codebase matures. . If you want GPU support, you should install the GPU version of TensorFlow with pip install tensorflow-gpu, or else you can use the CPU version using pip install tensorflow. Luminoth can also install TensorFlow for you if you install it with pip install luminoth[tf] or pip install luminoth[tf-gpu], depending on the version of TensorFlow you wish to use.Starting Price: Free -
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Kubeflow
Kubeflow
The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow provides a custom TensorFlow training job operator that you can use to train your ML model. In particular, Kubeflow's job operator can handle distributed TensorFlow training jobs. Configure the training controller to use CPUs or GPUs and to suit various cluster sizes. Kubeflow includes services to create and manage interactive Jupyter notebooks. You can customize your notebook deployment and your compute resources to suit your data science needs. Experiment with your workflows locally, then deploy them to a cloud when you're ready. -
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Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.
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Lunary
Lunary
Lunary is an AI developer platform designed to help AI teams manage, improve, and protect Large Language Model (LLM) chatbots. It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. Lunary's core platform is 100% open-source. Self-host or in the cloud, get started in minutes.Starting Price: $20 per month -
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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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Tensor
Tensor
Tensor's mission is to become the trading venue for the pro-NFT trader. We started Tensor become we ourselves were flipping NFTs daily and weren't satisfied with existing tooling. We wanted something faster, with better coverage, more data, and advanced order types, and so Tensor was born. When you go to Tensor you'll find a single coherent dApp, but under the hood, we actually have a few moving parts. Bonding-curve-based orders: linear & exponential, lets you DCA into/out of NFTs! Instant new collection listings (we appreciate traders want to always trade the latest stuff). Earn trading fees & LP rewards by providing liquidity and creating markets for your favorite NFT collections on TensorSwap. Market-makers are important because they make markets more liquid, meaning they let other traders enter/exit the market at a more favorable price. -
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Arch
Arch
Arch is an intelligent gateway designed to protect, observe, and personalize AI agents through seamless integration with your APIs. Built on Envoy Proxy, Arch offers secure handling, intelligent routing, robust observability, and integration with backend systems, all external to business logic. It features an out-of-process architecture compatible with various application languages, enabling quick deployment and transparent upgrades. Engineered with specialized sub-billion parameter Large Language Models (LLMs), Arch excels in critical prompt-related tasks such as function calling for API personalization, prompt guards to prevent toxic or jailbreak prompts, and intent-drift detection to enhance retrieval accuracy and response efficiency. Arch extends Envoy's cluster subsystem to manage upstream connections to LLMs, providing resilient AI application development. It also serves as an edge gateway for AI applications, offering TLS termination, rate limiting, and prompt-based routing.Starting Price: Free -
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TF-Agents
Tensorflow
TensorFlow Agents (TF-Agents) is a comprehensive library designed for reinforcement learning in TensorFlow. It simplifies the design, implementation, and testing of new RL algorithms by providing well-tested modular components that can be modified and extended. TF-Agents enables fast code iteration with good test integration and benchmarking. It includes a variety of agents such as DQN, PPO, REINFORCE, SAC, and TD3, each with their respective networks and policies. It also offers tools for building custom environments, policies, and networks, facilitating the creation of complex RL pipelines. TF-Agents supports both Python and TensorFlow environments, allowing for flexibility in development and deployment. It is compatible with TensorFlow 2.x and provides tutorials and guides to help users get started with training agents on standard environments like CartPole. -
34
LangDB
LangDB
LangDB offers a community-driven, open-access repository focused on natural language processing tasks and datasets for multiple languages. It serves as a central resource for tracking benchmarks, sharing tools, and supporting the development of multilingual AI models with an emphasis on openness and cross-linguistic representation.Starting Price: $49 per month -
35
DeepSeek V3.1
DeepSeek
DeepSeek V3.1 is a groundbreaking open-weight large language model featuring a massive 685-billion parameters and an extended 128,000‑token context window, enabling it to process documents equivalent to 400-page books in a single prompt. It delivers integrated capabilities for chat, reasoning, and code generation within a unified hybrid architecture, seamlessly blending these functions into one coherent model. V3.1 supports a variety of tensor formats to give developers flexibility in optimizing performance across different hardware. Early benchmark results show robust performance, including a 71.6% score on the Aider coding benchmark, putting it on par with or ahead of systems like Claude Opus 4 and doing so at a far lower cost. Made available under an open source license on Hugging Face with minimal fanfare, DeepSeek V3.1 is poised to reshape access to high-performance AI, challenging traditional proprietary models.Starting Price: Free -
36
JFrog ML
JFrog
JFrog ML (formerly Qwak) offers an MLOps platform designed to accelerate the development, deployment, and monitoring of machine learning and AI applications at scale. The platform enables organizations to manage the entire lifecycle of machine learning models, from training to deployment, with tools for model versioning, monitoring, and performance tracking. It supports a wide variety of AI models, including generative AI and LLMs (Large Language Models), and provides an intuitive interface for managing prompts, workflows, and feature engineering. JFrog ML helps businesses streamline their ML operations and scale AI applications efficiently, with integrated support for cloud environments. -
37
LiteRT
Google
LiteRT (Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. It enables developers to deploy machine learning models across various platforms and microcontrollers. LiteRT supports models from TensorFlow, PyTorch, and JAX, converting them into the efficient FlatBuffers format (.tflite) for optimized on-device inference. Key features include low latency, enhanced privacy by processing data locally, reduced model and binary sizes, and efficient power consumption. The runtime offers SDKs in multiple languages such as Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating integration into diverse applications. Hardware acceleration is achieved through delegates like GPU and iOS Core ML, improving performance on supported devices. LiteRT Next, currently in alpha, introduces a new set of APIs that streamline on-device hardware acceleration.Starting Price: Free -
38
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. -
39
Taam Cloud
Taam Cloud
Taam Cloud is a powerful AI API platform designed to help businesses and developers seamlessly integrate AI into their applications. With enterprise-grade security, high-performance infrastructure, and a developer-friendly approach, Taam Cloud simplifies AI adoption and scalability. Taam Cloud is an AI API platform that provides seamless integration of over 200 powerful AI models into applications, offering scalable solutions for both startups and enterprises. With products like the AI Gateway, Observability tools, and AI Agents, Taam Cloud enables users to log, trace, and monitor key AI metrics while routing requests to various models with one fast API. The platform also features an AI Playground for testing models in a sandbox environment, making it easier for developers to experiment and deploy AI-powered solutions. Taam Cloud is designed to offer enterprise-grade security and compliance, ensuring businesses can trust it for secure AI operations.Starting Price: $10/month -
40
Storm MCP
Storm MCP
Storm MCP is a gateway built around the Model Context Protocol (MCP) that lets AI applications connect to multiple verified MCP servers with one-click deployment, offering enterprise-grade security, observability, and simplified tool integration without requiring custom integration work. It enables you to standardize AI connections by exposing only selected tools from each MCP server, thereby reducing token usage and improving model tool selection. Through Lightning deployment, one can connect to over 30 secure MCP servers, while Storm handles OAuth-based access, full usage logs, rate limiting, and monitoring. It’s designed to bridge AI agents with external context sources in a secure, managed fashion, letting developers avoid building and maintaining MCP servers themselves. Built for AI agent developers, workflow builders, and indie hackers, Storm MCP positions itself as a composable, configurable API gateway that abstracts away infrastructure overhead and provides reliable context.Starting Price: $29 per month -
41
Disco.dev
Disco.dev
Disco.dev is an open source personal hub for MCP (Model Context Protocol) integration that lets users discover, launch, customize, and remix MCP servers with zero setup, no infrastructure overhead required. It provides plug‑and‑play connectors and a collaborative environment where users can spin up servers instantly via CLI or local execution, explore and remix community‑shared servers, and tailor them to unique workflows. This streamlined, infrastructure‑free approach accelerates AI automation development, democratizes access to agentic tooling, and fosters open collaboration across technical and non-technical contributors through a modular, remixable ecosystem.Starting Price: Free -
42
Promptmetheus
Promptmetheus
Compose, test, optimize, and deploy reliable prompts for the leading language models and AI platforms to supercharge your apps and workflows. Promptmetheus is an Integrated Development Environment (IDE) for LLM prompts, designed to help you automate workflows and augment products and services with the mighty capabilities of GPT and other cutting-edge AI models. With the advent of the transformer architecture, cutting-edge Language Models have reached parity with human capability in certain narrow cognitive tasks. But, to viably leverage their power, we have to ask the right questions. Promptmetheus provides a complete prompt engineering toolkit and adds composability, traceability, and analytics to the prompt design process to assist you in discovering those questions.Starting Price: $29 per month -
43
TensorStax
TensorStax
TensorStax is an AI-powered platform that automates data engineering tasks, enabling businesses to efficiently manage data pipelines, database migrations, ETL/ELT processes, and data ingestion within their cloud infrastructure. Its autonomous agents integrate seamlessly with existing tools like Airflow and dbt, facilitating end-to-end pipeline development and proactive issue detection to minimize downtime. Deployed within a company's Virtual Private Cloud (VPC), TensorStax ensures data security and privacy. By automating complex data workflows, it allows teams to focus on strategic analysis and decision-making. -
44
RouteLLM
LMSYS
Developed by LM-SYS, RouteLLM is an open-source toolkit that allows users to route tasks between different large language models to improve efficiency and manage resources. It supports strategy-based routing, helping developers balance speed, accuracy, and cost by selecting the best model for each input dynamically. -
45
Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
46
ToolSDK.ai
ToolSDK.ai
ToolSDK.ai is a free TypeScript SDK and marketplace that accelerates building agentic AI applications by providing instant access to over 5,300+ MCP (Model Context Protocol) servers and composable tools with one line of code, enabling developers to wire up real-world workflows combining language models with external systems. The platform exposes a unified client for loading packaged MCP servers (e.g., search, email, CRM, task management, storage, analytics) and converting them into OpenAI-compatible tools, handling authentication, invocation, and result orchestration so assistants can call, compare, and act on live data from services like Gmail, Salesforce, Google Drive, ClickUp, Notion, Slack, GitHub, analytics platforms, and custom web search or automation endpoints. It includes example quick-start integrations, supports metadata and conditional logic in multi-step orchestrations, and makes scaling to parallel agents and complex pipelines straightforward.Starting Price: Free -
47
IREN Cloud
IREN
IREN’s AI Cloud is a GPU-cloud platform built on NVIDIA reference architecture and non-blocking 3.2 TB/s InfiniBand networking, offering bare-metal GPU clusters designed for high-performance AI training and inference workloads. The service supports a range of NVIDIA GPU models with specifications such as large amounts of RAM, vCPUs, and NVMe storage. The cloud is fully integrated and vertically controlled by IREN, giving clients operational flexibility, reliability, and 24/7 in-house support. Users can monitor performance metrics, optimize GPU spend, and maintain secure, isolated environments with private networking and tenant separation. It allows deployment of users’ own data, models, frameworks (TensorFlow, PyTorch, JAX), and container technologies (Docker, Apptainer) with root access and no restrictions. It is optimized to scale for demanding applications, including fine-tuning large language models. -
48
ZBrain
ZBrain
Import data in any format, including text or images from any source like documents, cloud or APIs and launch a ChatGPT-like interface based on your preferred large language model like GPT-4, FLAN and GPT-NeoX and answer user queries based on the imported data. A comprehensive list of sample questions across various departments in different industries that can be asked to an LLM connected to a company’s private data source through ZBrain. Seamless integration of ZBrain as a prompt-response service into your existing tools and products. Enhance your deployment experience with secure options like ZBrain Cloud or the flexibility to self-host on a private infrastructure. ZBrain Flow empowers you to create business logic without writing any code. The intuitive flow interface allows you to connect multiple large language models, prompt templates, and image and video models with extraction and parsing tools to build powerful and intelligent applications. -
49
ZenMux
ZenMux
ZenMux is an enterprise-grade AI gateway that provides a unified interface for accessing and orchestrating multiple leading large language models through a single account and API. Instead of managing separate providers, keys, and integrations, users can connect to top models from companies like OpenAI, Anthropic, Google, and others through one consistent system, fully compatible with existing protocols such as OpenAI and Gemini Enterprise Agent Platform. It eliminates the complexity of multi-provider setups by offering intelligent routing that automatically selects the most suitable model for each task based on cost, performance, and reliability. ZenMux emphasizes direct access to official providers and authorized cloud partners, ensuring that all outputs come from authentic, high-quality sources without proxies or degraded versions. One of its defining features is a built-in AI model insurance, which detects issues.Starting Price: $20 per month -
50
Undrstnd
Undrstnd
Undrstnd Developers empowers developers and businesses to build AI-powered applications with just four lines of code. Experience incredibly fast AI inference times, up to 20 times faster than GPT-4 and other leading models. Our cost-effective AI services are designed to be up to 70 times cheaper than traditional providers like OpenAI. Upload your own datasets and train models in under a minute with our easy-to-use data source feature. Choose from a variety of open source Large Language Models (LLMs) to fit your specific needs, all backed by powerful, flexible APIs. Our platform offers a range of integration options to make it easy for developers to incorporate our AI-powered solutions into their applications, including RESTful APIs and SDKs for popular programming languages like Python, Java, and JavaScript. Whether you're building a web application, a mobile app, or an IoT device, our platform provides the tools and resources you need to integrate our AI-powered solutions seamlessly.
