Alternatives to ex5.ai

Compare ex5.ai alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to ex5.ai in 2026. Compare features, ratings, user reviews, pricing, and more from ex5.ai competitors and alternatives in order to make an informed decision for your business.

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    Compute with Hivenet
    Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe. Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint. Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside hivenet compute.
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    supercomputer

    supercomputer

    supercomputer

    supercomputer is a hosted cloud-compute service that provides GPU and CPU sessions for machine-learning and other compute-intensive workloads. Developers, researchers, and teams can launch and manage sessions from a command-line interface or Python SDK, run code on configurable GPU instances, and preserve workspace files between sessions. The service supports model training and fine-tuning, inference, experiments, evaluations, batch processing, hyperparameter sweeps, and data-processing jobs. Users can upload scripts and datasets, execute commands in persistent sessions, and retrieve results or save them in shared volumes. Compute charges accrue only while sessions are running, and stopped sessions retain their workspace for later use. The service uses prepaid credits and bills compute by the second, with rates varying by GPU configuration.
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    packet.ai

    packet.ai

    packet.ai

    packet.ai is a GPU cloud platform built to give developers and AI teams fast access to high-performance computing without the complexity and inefficiencies of traditional cloud infrastructure. It provides on-demand GPU instances, including modern NVIDIA hardware, that can be launched in seconds and accessed through tools like SSH, Jupyter, or VS Code, enabling users to quickly start training models, running inference, or experimenting with AI workloads. It introduces a different approach to GPU usage by dynamically allocating resources based on real-time workload demands, rather than treating a GPU as a fixed unit, allowing multiple compatible workloads to share hardware efficiently while maintaining predictable performance. This results in higher utilization and eliminates the need to pay for idle capacity, focusing instead on the exact compute resources consumed. packet.ai also offers an OpenAI-compatible API for language model inference, embeddings, and fine-tuning, etc.
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    GPUBank

    GPUBank

    GPU Compute

    GPUBank is a cloud GPU rental platform for developers, machine-learning practitioners, and research teams that need accelerated compute for AI and other GPU workloads. Through its web console, customers can select NVIDIA or AMD GPU instances, choose a deployment region, and start preconfigured environments for tasks such as model training, inference, fine-tuning, image generation, and framework development. Available templates include PyTorch, vLLM, ComfyUI, and Ollama. The service provides an API, command-line interface, Python SDK, and Terraform provider for provisioning and usage management. GPU compute is priced by the second, with the selected instance's CPU, memory, local NVMe storage, public IPv4, and network traffic included in the hourly rate; persistent disks are billed separately. Customers can use on-demand, interruptible, or reserved capacity across listed data-center regions.
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    BHK Cloud

    BHK Cloud

    BHK Cloud

    BHK Cloud is a Frankfurt-based cloud infrastructure platform for AI and data-intensive workloads. It provides on-demand RTX 3090 GPU compute with 24 GB VRAM starting at $0.15 per GPU hour, S3-compatible object storage from $2.50 per TB/month with zero egress fees, and managed AI agent hosting. Customers can provision resources through a REST API and CLI, launch preconfigured PyTorch, TensorFlow, and CUDA environments, attach storage volumes, and use existing S3 tools such as AWS CLI and boto3 through a compatible endpoint. Infrastructure is operated from Frankfurt for teams seeking European data residency, predictable usage-based pricing, and no minimum commitments. BHK Cloud supports model inference, image generation, LoRA or QLoRA fine-tuning, rendering, video processing, backups, archives, and large model or data pipelines.
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    NetMind AI

    NetMind AI

    NetMind AI

    NetMind.AI is a decentralized computing platform and AI ecosystem designed to accelerate global AI innovation. By leveraging idle GPU resources worldwide, it offers accessible and affordable AI computing power to individuals, businesses, and organizations of all sizes. The platform provides a range of services, including GPU rental, serverless inference, and an AI ecosystem that encompasses data processing, model training, inference, and agent development. Users can rent GPUs at competitive prices, deploy models effortlessly with on-demand serverless inference, and access a wide array of open-source AI model APIs with high-throughput, low-latency performance. NetMind.AI also enables contributors to add their idle GPUs to the network, earning NetMind Tokens (NMT) as rewards. These tokens facilitate transactions on the platform, allowing users to pay for services such as training, fine-tuning, inference, and GPU rentals.
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    GPU.ai

    GPU.ai

    GPU.ai

    GPU.ai is a cloud platform specialized in GPU infrastructure tailored to AI workloads. It offers two main products: GPU Instance, letting users launch compute instances with recent NVIDIA GPUs (for tasks like training, fine-tuning, and inference), and model inference, where you upload your pre-built models and GPU.ai handles deployment. The hardware options include H200s and A100s. It also supports custom requests via sales, with fast responses (within ~15 minutes) for more specialized GPU or workflow needs.
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    Scalattice

    Scalattice

    Robottik

    Scalattice is a managed inference API and distributed GPU network for developers running open models and GPU owners providing compute. Developers submit chat-completion and image-generation requests through OpenAI-compatible endpoints, choose catalog models, and manage API keys, credits, usage, model access, and regional policies through Scalattice Cloud or its command-line interface. Requests run on provider machines, and the service tracks usage and distributes provider payouts. GPU providers install the Scalattice agent on compatible Windows, Linux, or Apple Silicon macOS computers, set availability, and monitor jobs and earnings. The service is intended for application developers, AI builders, and GPU operators seeking hosted inference capacity or a way to contribute compute. Model availability and prices depend on the catalog and available capacity.
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    Core42

    Core42

    Core42

    Core42 delivers sovereign AI and cloud solutions that help individuals, enterprises, and nations unlock the full potential of AI through secure, scalable, and performance-driven infrastructure. Its AI Cloud is a full-stack platform built for the entire intelligence lifecycle, from data movement and training to optimization, fine-tuning, deployment, governance, and production inference. It gives AI builders access to leading accelerators, integrated tools, orchestration, high-performance storage, and expert support so they can train, fine-tune, and deploy agentic and inference workloads faster. Core42 AI Cloud supports GenAI services, model hosting and inference, AI operations, and infrastructure as a service, enabling teams to build and scale next-generation AI applications with confidence and speed. Its GenAI services help accelerate innovation with agents, retrieval-augmented generation, guardrails, and fine-tuning.
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    GreenNode

    GreenNode

    GreenNode

    GreenNode is a high-performance, self-service enterprise AI cloud platform that centralizes the full AI/ML model lifecycle, from development to deployment, on a scalable GPU-accelerated infrastructure designed for modern AI workloads. It provides cloud-hosted notebook instances where teams can write code, visualize data, and collaborate, supports model training and fine-tuning with flexible compute, and offers a model registry to manage versions and performance across deployments. It includes serverless AI model-as-a-service capabilities with a catalog of 20+ pre-trained open-source models for text generation, embeddings, vision, speech, and more that can be accessed through standard APIs for fast experimentation and integration into applications without building model infrastructure from scratch. GreenNode’s environment accelerates model inference with low-latency GPU execution, enables seamless integration with tools and frameworks, and features performance.
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    Replicate

    Replicate

    Replicate

    Replicate is a platform that enables developers and businesses to run, fine-tune, and deploy machine learning models at scale with minimal effort. It offers an easy-to-use API that allows users to generate images, videos, speech, music, and text using thousands of community-contributed models. Users can fine-tune existing models with their own data to create custom versions tailored to specific tasks. Replicate supports deploying custom models using its open-source tool Cog, which handles packaging, API generation, and scalable cloud deployment. The platform automatically scales compute resources based on demand, charging users only for the compute time they consume. With robust logging, monitoring, and a large model library, Replicate aims to simplify the complexities of production ML infrastructure.
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    Together AI

    Together AI

    Together AI

    Together AI provides an AI-native cloud platform built to accelerate training, fine-tuning, and inference on high-performance GPU clusters. Engineered for massive scale, the platform supports workloads that process trillions of tokens without performance drops. Together AI delivers industry-leading cost efficiency by optimizing hardware, scheduling, and inference techniques, lowering total cost of ownership for demanding AI workloads. With deep research expertise, the company brings cutting-edge models, hardware, and runtime innovations—like ATLAS runtime-learning accelerators—directly into production environments. Its full-stack ecosystem includes a model library, inference APIs, fine-tuning capabilities, pre-training support, and instant GPU clusters. Designed for AI-native teams, Together AI helps organizations build and deploy advanced applications faster and more affordably.
    Starting Price: $0.0001 per 1k tokens
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    Intel Tiber AI Cloud
    Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.
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    Pacific

    Pacific

    Pacific Intelligent Technologies

    Pacific provides GPU compute rental and modular AI infrastructure for organizations running AI training, fine-tuning and inference. Its catalog offers on-demand dedicated NVIDIA GPU nodes, including H100, H200 and B200 configurations, with larger systems and reserved capacity available by request. Rentals provide SSH access to bare-metal Linux hosts with NVIDIA drivers and CUDA. For longer-term or site-specific needs, Pacific offers reserved single-tenant clusters, managed on-premises deployments, colocation and bridge capacity while a permanent facility is prepared. Its factory-built modules combine compute, networking, cooling and power distribution for customer sites, colocation facilities or other suitable powered locations. Buyers include AI teams and infrastructure operators evaluating training or inference capacity, as well as organizations requiring greater control over compute deployment.
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    Synap

    Synap

    Linkrra LLC

    Synap is a hosted inference API that gives developers an OpenAI-compatible endpoint for open-weight language models. Applications can connect through familiar OpenAI SDKs and chat-completion requests by changing the API base URL, key and model name. Its catalog includes models such as Qwen3, Qwen3-VL, Qwen3 Coder, Gemma 4 and gpt-oss-20b, with model-specific input and output token rates. Synap supports streaming and tool calling, and applies zero data retention to requests. Developers can use prepaid credits that do not expire, monthly plans, or pay-per-call USDC payments through x402. The service is designed for software developers, AI application builders and teams integrating model inference into applications and agent workflows.
    Starting Price: $0.0675/1M input tokens
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    SiliconFlow

    SiliconFlow

    SiliconFlow

    SiliconFlow is a high-performance, developer-focused AI infrastructure platform offering a unified and scalable solution for running, fine-tuning, and deploying both language and multimodal models. It provides fast, reliable inference across open source and commercial models, thanks to blazing speed, low latency, and high throughput, with flexible options such as serverless endpoints, dedicated compute, or private cloud deployments. Platform capabilities include one-stop inference, fine-tuning pipelines, and reserved GPU access, all delivered via an OpenAI-compatible API and complete with built-in observability, monitoring, and cost-efficient smart scaling. For diffusion-based tasks, SiliconFlow offers the open source OneDiff acceleration library, while its BizyAir runtime supports scalable multimodal workloads. Designed for enterprise-grade stability, it includes features like BYOC (Bring Your Own Cloud), robust security, and real-time metrics.
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    HPC-AI

    HPC-AI

    HPC-AI

    HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.
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    Lium

    Lium

    lium.io

    Agent-first GPU cloud. Rent NVIDIA GPUs via web, CLI, SDK, or API. Providers earn 95% rental revenue + bonuses. lium.io connects developers, research teams and AI agents with independent GPU providers. Rent a single GPU or a full 8-GPU node for training, fine-tuning, inference and batch jobs, with SSH and Jupyter access. Deploy through the web, CLI, Python SDK, API or MCP integration. Billing is per second, with usage-based marketplace prices and no minimum commitment. View live rates and availability on the live pricing page; prices change with supply. Choose Secure or Spot GPU capacity to fit your workload. New accounts can receive $5 of credit after passing signup checks. Have idle GPUs? Set your own rental prices and list capacity in the provider portal. Documentation and developer guides are available.
    5.0 out of 5 stars 1 Rating for Lium
    Starting Price: $0.40 per GPU per hour
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    Confidential AI

    Confidential AI

    Confidential AI

    Confidential AI provides private inference, private agents, confidential VMs and confidential computing infrastructure for AI labs, inference providers, routers, and organizations handling sensitive workloads. Its hosted inference service runs open-weight models in hardware-backed trusted execution environments (TEEs), including Intel TDX and AMD SEV-SNP confidential VMs with NVIDIA GPUs in confidential computing mode. Prompts, responses, and workload data are protected from infrastructure operators, and clients can verify attestation before sending sensitive input. Customers can use an OpenAI-compatible API to deploy inference endpoints and agent workloads, or license the confidential-computing stack for on-premises infrastructure, bare metal, and major clouds. Use cases include serving models while limiting operator access to prompts and model assets, and running sensitive AI workloads on dedicated confidential compute.
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    Tinfoil

    Tinfoil

    Tinfoil

    Tinfoil is a verifiably private AI platform built to deliver zero-trust, zero-data-retention inference by running open-source or custom models inside secure hardware enclaves in the cloud, giving you the data-privacy assurances of on-premises systems with the scalability and convenience of the cloud. All user inputs and inference operations are processed in confidential-computing environments so that no one, not even Tinfoil or the cloud provider, can access or retain your data. It supports private chat, private data analysis, user-trained fine-tuning, and an OpenAI-compatible inference API, covers workloads such as AI agents, private content moderation, and proprietary code models, and provides features like public verification of enclave attestation, “provable zero data access,” and full compatibility with major open source models.
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    Nextify

    Nextify

    Nextify Now

    Nextify is a cloud infrastructure platform for provisioning and managing virtual machines, confidential-computing VMs, GPU instances, and related networking and storage. It offers shared- and dedicated-vCPU AMD EPYC machines, AMD SEV-SNP secure VMs with encrypted guest memory, a virtual TPM and remote attestation, and GPU VMs with AMD Radeon AI PRO R9700 cards. Customers can attach NVMe-backed block storage, create snapshots and S3-compatible object-storage buckets, and use public IPv4, firewalls, private networks, VPN gateways and load balancers. Resources can be managed in the web portal or through a REST API and command-line client; the API also supports automation from scripts, CI pipelines and Terraform. Compute instances are billed hourly up to a published monthly cap, with plans for web services, development and test environments, databases, build jobs, GPU inference, fine-tuning and rendering workloads.
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    NeevCloud

    NeevCloud

    NeevCloud

    NeevCloud is a full-stack AI SuperCloud for building, training, fine-tuning, and deploying AI models at scale. Access GPU AI Services powered by NVIDIA H100, B200, and GB200 NVL72; a pay-per-token Model API supporting Llama 3, Mixtral, Qwen, and Stable Diffusion; and Agentic Studio for building, testing, and shipping AI agents with built-in governance and observability. The platform is Kubernetes-native, OpenAI-compatible, and designed for zero lock-in with no egress fees and transparent pricing. Cloud Servers, Snapshots, Load Balancers, and Orchestration round out the IaaS layer. S3-compatible object storage is available through Zata.ai. NeevCloud owns every infrastructure layer, from GPU clusters to AI orchestration software, delivering strong price-to-performance, data sovereignty, and instant GPU access with no waiting lists. Built for AI startups, ML engineers, data scientists, enterprises, and research institutions scaling AI workloads.
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    Tuning Engines

    Tuning Engines

    CerebrixOS

    Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems. It brings together the full AI lifecycle in one governed platform: inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations. Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform.
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    FPT Cloud

    FPT Cloud

    FPT Cloud

    FPT Cloud is a next‑generation cloud computing and AI platform that streamlines innovation by offering a robust, modular ecosystem of over 80 services, from compute, storage, database, networking, and security to AI development, backup, disaster recovery, and data analytics, built to international standards. Its offerings include scalable virtual servers with auto‑scaling and 99.99% uptime; GPU‑accelerated infrastructure tailored for AI/ML workloads; FPT AI Factory, a comprehensive AI lifecycle suite powered by NVIDIA supercomputing (including infrastructure, model pre‑training, fine‑tuning, model serving, AI notebooks, and data hubs); high‑performance object and block storage with S3 compatibility and encryption; Kubernetes Engine for managed container orchestration with cross‑cloud portability; managed database services across SQL and NoSQL engines; multi‑layered security with next‑gen firewalls and WAFs; centralized monitoring and activity logging.
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    Radiant

    Radiant

    Radiant

    Radiant is a fully integrated AI infrastructure platform designed to deliver end-to-end capabilities for building and scaling AI systems. It combines compute, software, energy, and capital into a unified ecosystem, enabling organizations to move from concept to deployment efficiently. Radiant’s AI Cloud includes NVIDIA-accelerated computing along with MLOps tools such as inference, fine-tuning, model registry, and serverless Kubernetes. Its proprietary software platform supports intelligent scheduling, automated node management, and secure multi-tenancy for large-scale operations. With infrastructure designed to scale from thousands to over 100,000 GPUs, Radiant ensures consistent performance and operational control. The platform also integrates energy solutions through its powered-land portfolio, optimizing costs and sustainability. Backed by significant capital resources, Radiant can support large-scale AI initiatives globally.
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    WhollyAPI

    WhollyAPI

    WhollyAPI

    WhollyAPI is a hosted AI inference platform that gives developers a unified API for using AI models in applications and workflows. Its model catalog includes text generation, embeddings, image generation, video generation, speech synthesis and recognition, and other multimodal tasks. Model pages provide model information, usage demonstrations, API compatibility details, and usage-based pricing; text-generation pages document OpenAI-compatible chat-completion requests through WhollyAPI's serverless API. The service is aimed at developers and teams building AI-enabled software who want to access multiple model types through one hosted service instead of operating inference infrastructure themselves. Potential uses include generating or transforming text and images, creating video, processing audio, and adding model-powered features to applications. Available models, capabilities, and charges vary by model and usage.
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    Nscale

    Nscale

    Nscale

    Nscale is the Hyperscaler engineered for AI, offering high-performance computing optimized for training, fine-tuning, and intensive workloads. From our data centers to our software stack, we are vertically integrated in Europe to provide unparalleled performance, efficiency, and sustainability. Access thousands of GPUs tailored to your requirements using our AI cloud platform. Reduce costs, grow revenue, and run your AI workloads more efficiently on a fully integrated platform. Whether you're using Nscale's built-in AI/ML tools or your own, our platform is designed to simplify the journey from development to production. The Nscale Marketplace offers users access to various AI/ML tools and resources, enabling efficient and scalable model development and deployment. Serverless allows seamless, scalable AI inference without the need to manage infrastructure. It automatically scales to meet demand, ensuring low latency and cost-effective inference for popular generative AI models.
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    Baseten

    Baseten

    Baseten

    Baseten is a high-performance platform designed for mission-critical AI inference workloads. It supports serving open-source, custom, and fine-tuned AI models on infrastructure built specifically for production scale. Users can deploy models on Baseten’s cloud, their own cloud, or in a hybrid setup, ensuring flexibility and scalability. The platform offers inference-optimized infrastructure that enables fast training and seamless developer workflows. Baseten also provides specialized performance optimizations tailored for generative AI applications such as image generation, transcription, text-to-speech, and large language models. With 99.99% uptime, low latency, and support from forward deployed engineers, Baseten aims to help teams bring AI products to market quickly and reliably.
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    Run BiOS

    Run BiOS

    UltraSafe AI Inc.

    Run BiOS is serverless, OpenAI-compatible inference. Point the OpenAI SDK at the Run BiOS endpoint and keep your code. Six model families — Claude, DeepSeek, GLM, Kimi, MiniMax and Qwen — plus bios-adaptive, which routes each request for quality, speed and budget against a published price ceiling. Prompts and responses live in memory and are discarded when the request completes: no request logs, no content store, no archive. Fine-tuning and dedicated GPU endpoints run from the same account if you later want weights you own, billed per second of GPU time. Pricing is usage-based from a pre-paid balance, published per million tokens, and an endpoint pauses rather than running up a debt if the balance reaches zero.
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    Nebius Token Factory
    Nebius Token Factory is a scalable AI inference platform designed to run open-source and custom AI models in production without manual infrastructure management. It offers enterprise-ready inference endpoints with predictable performance, autoscaling throughput, and sub-second latency — even at very high request volumes. It delivers 99.9% uptime availability and supports unlimited or tailored traffic profiles based on workload needs, simplifying the transition from experimentation to global deployment. Nebius Token Factory supports a broad set of open source models such as Llama, Qwen, DeepSeek, GPT-OSS, Flux, and many others, and lets teams host and fine-tune models through an API or dashboard. Users can upload LoRA adapters or full fine-tuned variants directly, with the same enterprise performance guarantees applied to custom models.
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    Overmind

    Overmind

    Overmind

    Overmind is a model training and deployment platform for teams building AI agents. It ingests production traces through OpenTelemetry and creates datasets from trace data, file uploads, and connectors for Langfuse, LangSmith, Braintrust, and Galileo. Teams can inspect agent context and runtime behavior, prepare and score datasets, evaluate prompts and models against their own examples, and optimize agent behavior through scored changes. The platform supports LoRA and full fine-tuning of open-weight models, benchmarking with configured evaluators, and deployment through an OpenAI-compatible endpoint; trained weights can also be downloaded. Users can work in the hosted console or run the platform on their own infrastructure with Docker Compose. It is designed for AI engineering and product teams operating agents in production that want to test, improve, or specialize models using their own data.
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    Amazon SageMaker HyperPod
    Amazon SageMaker HyperPod is a purpose-built, resilient compute infrastructure that simplifies and accelerates the development of large AI and machine-learning models by handling distributed training, fine-tuning, and inference across clusters with hundreds or thousands of accelerators, including GPUs and AWS Trainium chips. It removes the heavy lifting involved in building and managing ML infrastructure by providing persistent clusters that automatically detect and repair hardware failures, automatically resume workloads, and optimize checkpointing to minimize interruption risk, enabling months-long training jobs without disruption. HyperPod offers centralized resource governance; administrators can set priorities, quotas, and task-preemption rules so compute resources are allocated efficiently among tasks and teams, maximizing utilization and reducing idle time. It also supports “recipes” and pre-configured settings to quickly fine-tune or customize foundation models.
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    distil labs

    distil labs

    distil labs

    distil labs optimizes AI workloads by replacing expensive frontier-model calls with custom small language models tuned to a specific task while maintaining the required quality bar. It observes real production traffic, captures traces from existing LLM requests, and automatically builds an evaluation set to understand how the workload actually behaves. It then generates and validates synthetic training data, matches the data distribution to the target workload, performs supervised fine-tuning and reinforcement learning, quantizes the model, and deploys an optimized endpoint. Results are automatically evaluated against the current model on accuracy, latency, and efficiency before teams choose to scale traffic. The resulting OpenAI-compatible endpoint combines a specialized SLM, prompt optimization, caching, and tuned serving for the use case.
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    kluster.ai

    kluster.ai

    kluster.ai

    Kluster.ai is a developer-centric AI cloud platform designed to deploy, scale, and fine-tune large language models (LLMs) with speed and efficiency. Built for developers by developers, it offers Adaptive Inference, a flexible and scalable service that adjusts seamlessly to workload demands, ensuring high-performance processing and consistent turnaround times. Adaptive Inference provides three distinct processing options: real-time inference for ultra-low latency needs, asynchronous inference for cost-effective handling of flexible timing tasks, and batch inference for efficient processing of high-volume, bulk tasks. It supports a range of open-weight, cutting-edge multimodal models for chat, vision, code, and more, including Meta's Llama 4 Maverick and Scout, Qwen3-235B-A22B, DeepSeek-R1, and Gemma 3 . Kluster.ai's OpenAI-compatible API allows developers to integrate these models into their applications seamlessly.
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    gpu.nz

    gpu.nz

    Transtrade

    gpu.nz is a cloud GPU rental service for developers, machine-learning engineers, researchers and creators who need on-demand compute for AI inference, model training, image and video generation, and rendering. Users compare GPU offers by model, memory, location and hourly rate, then launch servers with preconfigured environments such as ComfyUI, Stable Diffusion Forge, Ollama with Open WebUI, vLLM, PyTorch and Jupyter, or use a custom Docker image. GPU time is billed by the minute from a prepaid balance; the rate is fixed when a server starts, and stopping it ends GPU charges while disk storage remains billable. A web console, REST API, command-line tool and hosted Model Context Protocol server support manual and scripted server search, launch and management.
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    IREN Cloud
    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.
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    Fortanix Confidential AI
    Fortanix Confidential AI is a unified platform that enables data teams to process sensitive datasets and run AI/ML models entirely within confidential computing environments, combining managed infrastructure, software, and workflow orchestration to maintain organizational privacy compliance. The service offers readily available, on-demand infrastructure powered by Intel Ice Lake third-generation scalable Xeon processors and supports execution of AI frameworks inside Intel SGX and other enclave technologies with zero external visibility. It delivers hardware-backed proofs of execution and detailed audit logs for stringent regulatory requirements, secures every stage of the MLOps pipeline, from data ingestion via Amazon S3 connectors or local uploads through model training, inference, and fine-tuning, and provides broad model compatibility.
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    NVIDIA Brev
    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.
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    Helix AI

    Helix AI

    Helix AI

    Build and optimize text and image AI for your needs, train, fine-tune, and generate from your data. We use best-in-class open source models for image and language generation and can train them in minutes thanks to LoRA fine-tuning. Click the share button to create a link to your session, or create a bot. Optionally deploy to your own fully private infrastructure. You can start chatting with open source language models and generating images with Stable Diffusion XL by creating a free account right now. Fine-tuning your model on your own text or image data is as simple as drag’n’drop, and takes 3-10 minutes. You can then chat with and generate images from those fine-tuned models straight away, all using a familiar chat interface.
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    Kunavo

    Kunavo

    Kunavo

    Kunavo is a hosted AI API gateway for developers and teams that need one account, API key, and prepaid balance to access models from multiple providers. It provides OpenAI-compatible Chat Completions and a native Anthropic Messages endpoint, with model identifiers and supported features described in its live catalog and API documentation. Depending on model and route, the service handles text, image, video, and audio requests. Developers connect supported SDKs, coding agents, workflow tools, and other clients by setting a base URL, key, and model identifier. A dashboard records request usage and costs; API keys can have per-key spending limits and IP allowlists. Billing is usage-based against prepaid credit, with published rates varying by model and modality and no recurring subscription. Use cases include adding model inference to applications, coding workflows, automations, and AI-powered customer-support or data-processing features.
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    DeepInfra

    DeepInfra

    DeepInfra

    DeepInfra is an AI inference cloud that makes it simple to run the latest machine learning models at scale, including LLMs, vision models, embeddings, image generation, video generation, speech, and more. It provides serverless inference through simple APIs, allowing developers to integrate production-ready AI models without managing GPU infrastructure, autoscaling, deployment complexity, or model hosting operations. DeepInfra supports OpenAI-compatible APIs for LLMs and embeddings, making it easier to switch from existing OpenAI-style integrations while accessing a broad catalog of open and commercial models. Its Native API gives access to every model type available on the platform, including image generation, speech recognition, object detection, token classification, fill-mask, image classification, zero-shot image classification, and text classification. DeepInfra is optimized for scalable, low-latency inference and runs models on high-performance GPU infrastructure.
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    BlackBit VOID
    BlackBit VOID is a hosted AI inference gateway and OpenAI-compatible API for developers, security teams, and researchers. It provides a shared endpoint and web console for using a catalog of language and multimodal models, including models aimed at authorized cybersecurity testing alongside general coding and reasoning models. Teams can create API keys, browse model capabilities and per-token rates, try requests in a playground, manage usage and prepaid credits, and connect compatible SDKs, IDEs, and agent frameworks. Common uses include application development, code review, security research, and authorized red-team workflows. VOID is accessed through its hosted API and browser console, with model-specific pay-as-you-go token pricing rather than a fixed subscription. Security testing should be limited to systems users own or are authorized to assess.
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    Simplismart

    Simplismart

    Simplismart

    Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go.
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    Axe Compute

    Axe Compute

    Axe Compute

    Axe Compute delivers enterprise bare-metal GPU infrastructure for AI and machine learning workloads with global reach, dedicated clusters, and predictable access. It gives teams dedicated GPU clusters delivered in approximately 48 hours across 200+ locations, with full choice across region, GPU type, fabric, interconnect, and topology. It is built to address the hidden cost of scaling AI: provisioning delays, limited cloud availability, quota rejections, rigid provider economics, data movement costs, and performance loss from virtualization. Axe provides 100% bare-metal access with zero virtualization overhead and no noisy neighbors, helping teams run LLM training, inference, diffusion, fine-tuning, enterprise deployment, and other AI workloads with more control. Its distributed GPU backbone supports low-latency placement near users and data, reducing the need to move data into centralized cloud regions.
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    LLaMA-Factory

    LLaMA-Factory

    hoshi-hiyouga

    ​LLaMA-Factory is an open source platform designed to streamline and enhance the fine-tuning process of over 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It supports various fine-tuning techniques, including Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, allowing users to customize models efficiently. It has demonstrated significant performance improvements; for instance, its LoRA tuning offers up to 3.7 times faster training speeds with better Rouge scores on advertising text generation tasks compared to traditional methods. LLaMA-Factory's architecture is designed for flexibility, supporting a wide range of model architectures and configurations. Users can easily integrate their datasets and utilize the platform's tools to achieve optimized fine-tuning results. Detailed documentation and diverse examples are provided to assist users in navigating the fine-tuning process effectively.
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    Runcrate

    Runcrate

    Aeonmind LLC

    Runcrate gives AI teams and their agents GPUs and inference from one account. Instances: rent a GPU by the hour (H100, H200, A100, L40S, RTX 4090, RTX PRO 6000 and more, 20+ models) with SSH, Jupyter and VS Code in the browser. A launch reaches running in about four minutes, booting is never billed, and most GPUs bill by the second. Inference: 200+ open models (DeepSeek, Qwen, Llama, Kimi, FLUX, Whisper) behind one OpenAI-compatible API, so the client you already use works. Priced per token, image or second. Storage volumes keep datasets and checkpoints between instances, and reserved clusters cover 8+ GPUs or month-long terms. Built for agents: connect Claude Code, Codex or Cursor to the Runcrate MCP server with one command and sign in through your browser, no key to paste. Your agent can then launch a GPU, run commands on it and shut it down. Also a CLI (brew install runcrateai/tap/runcrate) and Python and TypeScript SDKs.
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    prompteasy.ai

    prompteasy.ai

    prompteasy.ai

    You can now fine-tune GPT with absolutely zero technical skills. Enhance AI models by tailoring them to your specific needs. Prompteasy.ai helps you fine-tune AI models in a matter of seconds. We make AI tailored to your needs by helping you fine-tune it. The best part is, that you don't even have to know AI fine-tuning. Our AI models will take care of everything. We will be offering prompteasy for free as part of our initial launch. We'll be rolling out pricing plans later this year. Our vision is to make AI smart and easily accessible to anyone. We believe that the true power of AI lies in how we train and orchestrate the foundational models, as opposed to just using them off the shelf. Forget generating massive datasets, just upload relevant materials and interact with our AI through natural language. We take care of building the dataset ready for fine-tuning. You just chat with the AI, download the dataset, and fine-tune GPT.
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    Ilus AI

    Ilus AI

    Ilus AI

    The quickest way to get started with our illustration generator is to use pre-made models. If you want to depict a style or an object that is not available in the premade models you can train your own fine tune by uploading 5-15 illustrations. there are no limits to fine-tuning you can use it for illustrations icons or any assets you need. Read more about fine-tuning. Illustrations are exportable in PNG and SVG formats. Fine-tuning allows you to train the stable-diffusion AI model, on a particular object or style, and create a new model that generates images of those objects or styles. The fine-tuning will be only as good as the data you provide. Around 5-15 images are recommended for fine-tuning. Images can be of any unique object or style. Images should contain only the subject itself, without background noise or other objects. Images must not include any gradients or shadows if you want to export it as SVG later. PNG export still works fine with gradients and shadows.
    Starting Price: $0.06 per credit
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    NVIDIA Confidential Computing
    NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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    Llama 2
    The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.