Listed together in guide “AI platforms and infrastructure”
AWS portfolio of Amazon-built foundation models and services for text, multimodal, speech, custom model building, and UI-automating agents.
Paid
Use cases
- Cost-sensitive chat, summarization, and multimodal analysis on AWS
- Building a custom frontier model with Nova Forge
- Automating production UI workflows with Nova Act agents
Pricing: Amazon Nova is billed through AWS, typically via Amazon Bedrock, with usage-based pricing that varies by model and service.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-09-04.
Listed together in guide “AI platforms and infrastructure”
Google Cloud's platform for building and running AI models and agents, branded Gemini Enterprise Agent Platform (formerly Vertex AI).
Paid
Use cases
- Enterprise generative AI apps on Google Cloud
- Custom model training and tuning at scale
- Production MLOps and model monitoring
Pricing: Pricing is usage-based through Google Cloud, varying by model, training, and serving resources; new customers receive free credits.
Sources
This record was last reviewed on 2026-09-10.
Listed together in guide “AI platforms and infrastructure”
Microsoft's Azure platform for building, evaluating, and deploying AI applications and agents, branded Microsoft Foundry (formerly Azure AI Foundry).
Paid
Use cases
- Building enterprise copilots and agents
- Evaluating and comparing models before deployment
- Governed AI deployment with Azure compliance
Pricing: Pricing is usage-based through Azure, varying by model and service; many tools have no separate platform fee.
Sources
This record was last reviewed on 2026-10-09.
Compared on “Fireworks AI vs Together AI vs Amazon Bedrock”
Inference platform for fast serving and fine-tuning of open-source generative AI models.
Paid
Use cases
- Serving open models in production with low latency
- Fine-tuning models on custom data
- Migrating from closed APIs with minimal code change
Pricing: Pricing is usage-based per token, with dedicated capacity options; new developers receive free credits.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-09-10.
Compared on “Fireworks AI vs Together AI vs Amazon Bedrock”
Cloud platform for running, fine-tuning, and hosting open-source AI models via serverless and dedicated endpoints.
Paid
Use cases
- Serving open models without managing GPUs
- Fine-tuning models on proprietary data
- Scaling inference for production applications
Pricing: Pricing is usage-based: per-token for serverless endpoints and per GPU hour for dedicated capacity; free credits are offered for new users.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-10-09.
Related: shares the task Running models yourself
AI cloud platform for workloads from training through inference, with NVIDIA GPU instances billed per GPU-hour, managed Kubernetes and Slurm, and token-based inference services.
Paid
Use cases
- Training and fine-tuning models on GPU clusters
- Running production inference for AI applications
- Scaling containerized workloads with managed Kubernetes or Slurm
Pricing: Pricing is usage-based: GPU compute per GPU-hour, plus storage and networking, with token-based inference on Token Factory. Some services are listed as free and promo credits are available, but there is no general free tier.
Pricing ↗ · Documentation ↗ · Sources
This record was last reviewed on 2026-10-09.
Related: shares the task Running models yourself
AI cloud provider offering GPU clusters, managed Kubernetes and Slurm, and a serverless inference API compatible with OpenAI SDKs.
Paid
Use cases
- Training and fine-tuning models on GPU clusters
- Running inference through a serverless, OpenAI-compatible API
- Operating containerized workloads on managed Kubernetes or Slurm
Pricing: Nscale does not publish a pricing page. Serverless inference is billed pay-as-you-go per token or request, compute is also available through reservations, and new accounts receive a small free credit according to the documentation.
Documentation ↗ · Sources
This record was last reviewed on 2026-09-10.
Related: shares the task Running models yourself
Platform for deploying and serving machine-learning models as scalable APIs.
Paid
Use cases
- Serving custom and open models in production
- Low-latency inference APIs
- Scaling ML services reliably
Pricing: Dedicated GPU compute is billed per minute with no charge for idle time, model APIs are billed per million tokens, and new accounts come with credits.
Documentation ↗ · Sources
This record was last reviewed on 2026-10-09.