AI private LLM hosting

Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).

Serverless GPUs and infra for training & serving ML.

Build and scale generative AI applications with foundation models

Google Cloud's unified platform for building, deploying, and scaling enterprise AI agents and models.

Enterprise AI platform for building, deploying, and governing models and agents

Enterprise AI platform combining AutoML, generative AI, and vertical agents for regulated industries.

Meta's open-weight LLM family covering 1B mobile models up to 405B frontier and natively multimodal 10M-context Llama 4 variants.

Desktop app for discovering, downloading, and running open-weight LLMs locally with an OpenAI-compatible server.

On-demand GPU cloud and serverless inference platform built specifically for AI workloads.

Open-source high-throughput inference engine for serving LLMs with PagedAttention and continuous batching.

Open-source framework and managed platform for serving and scaling AI models in production.

AI-native GPU cloud built for large-scale training, fine-tuning, and inference on NVIDIA hardware.

Secure, isolated sandboxes for running AI-generated code with sub-90ms cold starts.

Open-source high-throughput inference engine for LLMs and multimodal models with OpenAI-compatible serving.

On-demand NVIDIA GPU cloud built specifically for training, fine-tuning, and serving large AI models.

Self-hosted OpenAI-compatible API for running LLMs, image, and audio models on your own hardware.

Managed fine-tuning platform for open-source LLMs and vision models with LoRA, full fine-tuning, and RL support.

Ray-powered platform for training, serving, and scaling LLMs.

Production inference and fine-tuning platform for open-source LLMs, tuned for speed and enterprise economics.

Memory-tuning platform for grounding LLMs in your facts.

Enterprise ModelOps platform for deploying and running AI/ML models across cloud, on-prem, and edge.

Native macOS LLM inference server built on MLX, with paged SSD KV caching for Apple Silicon agents.

Distributed training, fine-tuning, and serving platform with federated learning roots.

Kubernetes-native MLOps platform for deploying and orchestrating ML and generative AI models in production.

MLOps platform for versioned pipelines, distributed training, and LLM evaluation across any cloud.

Serverless GPU infrastructure for AI workloads with sub-second cold starts and bring-your-own-cloud support.

Enterprise AI platform for building, deploying, and governing models and agents at scale.

Open-source framework for building, deploying, and scaling AI microservices across text, vision, and audio.

The de facto runtime for running open-weights LLMs locally, now with a paid cloud tier for bigger models.

End-to-end MLOps platform with GPU notebooks, training jobs, and model deployment, now folded into DigitalOcean.

Production AI inference platform for deploying and monitoring models across cloud, on-prem, and edge.

Enterprise MLOps and GenAI platform for taking models from notebook to production at scale.

Infrastructure-agnostic MLOps platform for the full ML/DL lifecycle across public, hybrid, and on-prem clouds.

Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.

AWS's end-to-end platform for building, training, and deploying machine learning models and AI agents at enterprise scale.

Fine-tune and serve open-source LLMs on your own data without managing GPUs.

Open-source Python framework for serving multimodal AI models as scalable gRPC/HTTP microservices.

Open-source sandbox infrastructure for running AI-generated code, agents, and browsers in isolated Docker or Kubernetes environments.

Production-ready, air-gapped RAG framework for querying your documents with local LLMs.

Open-source tool that auto-packages ML models into production-ready Docker containers with a prediction API.

Sovereign enterprise platform for building, deploying, and governing AI agents on your own infrastructure.

Enterprise control plane for deploying, governing, and scaling agentic AI on your own infrastructure.

Self-hosted AI control plane that lets regulated enterprises govern models, agents, and MCP servers behind their firewall.

An open-source optimization layer that sits between your app and Ollama to squeeze more performance out of local LLMs.

One API, 200+ models, transparent pricing, and no vendor lock-in.

Match LLMs to GPUs and plan multi-model AI stacks by VRAM, bandwidth and precision.

Self-hosted, extensible AI chat platform that runs on your infrastructure

Physics-based calculator that predicts LLM decode speed, memory fit, and quantization quality on any hardware.