Platform Tools
🤖
Together AI
Paid
Together AI is a cloud platform for running and fine-tuning open-source large language models at scale with an API-first interface that mirrors OpenAI's API for easy migration. It offers dedicated and serverless inference for models like Llama, Mistral, Qwen, and DeepSeek at significantly lower cost than proprietary alternatives, along with fine-tuning infrastructure and a model hub. AI startups and enterprise ML teams use Together AI to build LLM-powered products on open models without managing GPU infrastructure.
🤖
Replicate
Paid
Replicate is a cloud platform that makes it easy to run machine learning models via a simple API without managing GPU infrastructure. It hosts thousands of open-source models for image generation, video creation, audio processing, and NLP tasks, and allows developers to deploy their own models with a single CLI command. Developers and product teams use Replicate to integrate state-of-the-art ML capabilities into applications quickly without hiring dedicated ML infrastructure engineers.
🤖
Modal
Paid
Modal is a serverless cloud platform designed for data and AI teams to run Python functions at scale without managing servers, containers, or Kubernetes. It provides on-demand GPU access, persistent volumes, scheduled jobs, and web endpoint deployment through a clean Python SDK. ML engineers and data scientists use Modal to run training jobs, batch inference, and data pipelines that scale from zero to hundreds of GPUs in seconds with pay-per-second billing.
🤖
Baseten
Paid
Baseten is an ML model serving platform that enables teams to deploy, scale, and monitor machine learning models with production-grade infrastructure including autoscaling, A/B testing, and observability built in. It provides model templates for popular architectures and a Truss open-source packaging format for reproducible deployments. ML platform teams at AI-first companies use Baseten to manage the full model serving lifecycle from staging to high-traffic production without building custom serving infrastructure.
🤖
Mystic
Paid
Mystic is a GPU cloud platform focused on running AI inference workloads for image, video, and audio generation models at competitive pricing with fast cold-start times. It provides a simple API for running diffusion models, video generation pipelines, and audio processing tasks without infrastructure overhead. Creative AI startups and media technology companies use Mystic to power generative media features in their products at the scale and speed their users demand.
🤖
CoreWeave
Paid
CoreWeave is a specialized cloud provider purpose-built for GPU-intensive AI and ML workloads, offering NVIDIA GPU clusters including H100, A100, and RTX series instances with bare-metal performance and Kubernetes-native orchestration. It provides significantly lower latency and higher GPU availability than general-purpose cloud providers, making it the preferred infrastructure partner for AI labs, model training companies, and inference providers. AI companies training large foundation models and running high-throughput inference use CoreWeave for its GPU density, networking performance, and AI-optimized storage.
🤖
Lambda Labs
Paid
Lambda Labs is a GPU cloud platform and hardware provider offering on-demand and reserved NVIDIA GPU instances optimized for deep learning training and inference at competitive pricing. Its cloud platform supports Jupyter notebooks, SSH access, persistent storage, and team collaboration features, making it accessible for both research and production workloads. AI researchers, ML engineers, and startups use Lambda Labs to access high-performance GPU compute without the complexity and cost overhead of general-purpose cloud providers.
🤖
Gradient
Paid
Gradient is an AI platform that enables enterprises to fine-tune, deploy, and run large language models on private infrastructure with complete data privacy. It provides a simple API for fine-tuning open-source models on proprietary data and deploying them as secure, dedicated endpoints without data leaving the organization's environment. Enterprise teams in legal, finance, and healthcare that need LLM capabilities without sharing sensitive data with third-party AI providers use Gradient to build private, customized AI applications.
🤖
Hugging Face Inference API
Freemium
Hugging Face Inference API provides serverless access to thousands of open-source ML models hosted on the Hugging Face Hub through a simple REST API, covering NLP, computer vision, audio, and multimodal tasks. Developers can run inference on state-of-the-art models without managing any infrastructure, paying only for the compute used per request. Startups and developers prototyping AI features use the Hugging Face Inference API to integrate ML model capabilities into applications quickly before committing to dedicated infrastructure for production scale.
🤖
Fireworks AI
Paid
Fireworks AI is a generative AI inference platform that provides fast API access to open-source LLMs including Llama, Mixtral, and Qwen at prices significantly below major cloud providers, with sub-100ms time-to-first-token on most models. Its FireFunction models support reliable function calling for agentic applications, and its on-demand fine-tuning service enables custom model deployment within hours. AI startups and enterprise teams building latency-sensitive LLM applications use Fireworks AI to achieve the response speed and cost efficiency their production applications demand.
🤖
OctoAI
Paid
OctoAI is a compute service platform that enables AI teams to run, tune, and scale AI models with optimized inference infrastructure delivering fast, cost-efficient performance. It specializes in media generation models including image, video, and 3D generation alongside LLM inference, providing a unified platform for multimodal AI applications. Product teams and AI startups building generative media and language applications use OctoAI to achieve production-grade performance and reliability without building and maintaining custom GPU serving infrastructure.
🤖
Anyscale
Paid
Anyscale is a managed platform built on Ray, the open-source distributed computing framework, that enables data science and ML engineering teams to scale Python workloads including model training, batch inference, and ML serving from a laptop to a large cluster without changing application code. It provides a fully managed Ray cluster environment with autoscaling, monitoring, and cost optimization tools that eliminate the infrastructure management burden of self-managed Ray deployments. AI companies training large models, running large-scale data processing, and serving high-throughput inference use Anyscale to focus on ML work rather than distributed systems engineering.
Browse Other Categories
Image Generation
Video AI
Productivity
AI Tool
Writing & Content
Audio & Music
Code & Developer
AI Companion
Gaming AI
LLM & Models
Data & Analytics
Finance
Framework
Marketing
Education
Legal
MLOps
Security
Directory
E-commerce
AI Agents
APIs
Automation
Cybersecurity AI
Database
Healthcare AI
HR & Recruiting
NLP
Real Estate AI
Research
Search