What should I use for model hosting if I want low ops?

If your goal is low ops, you generally want a managed model hosting or serverless inference option rather than running your own GPUs.

Best low-ops options

1. Managed inference APIs

Use a hosted API from providers like:

• OpenAI
• Anthropic
• Google Gemini
• Mistral API
• Cohere

Pros: almost zero infrastructure work, automatic scaling, monitoring handled for you
Cons: less control, can get expensive at scale, vendor lock-in

Best for: most apps that just need reliable model access with minimal maintenance

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2. Serverless model hosting platforms

These let you deploy open-source models without managing servers:

• Hugging Face Inference Endpoints
• Replicate
• Modal
• Together.ai
• Fireworks.ai
• Baseten
• Groq for very fast inference on supported models

Pros: easier than self-hosting, usually handles scaling and deployment
Cons: still some platform-specific setup, costs can vary, model options may be limited

Best for: open-source models with low operational burden

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3. Cloud-managed AI services

From major clouds:

• AWS Bedrock
• Azure OpenAI
• Google Vertex AI
• AWS SageMaker endpoints (more ops than Bedrock, but still managed)

Pros: enterprise-friendly, integrates well with existing cloud setup, governance/security features
Cons: can be more complex than pure API providers

Best for: teams already on a major cloud or needing compliance/security controls

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If you want the simplest answer

• For easiest overall: use a hosted API like OpenAI/Anthropic/Gemini
• For open-source models with low ops: use Hugging Face Inference Endpoints, Modal, or Together.ai
• For enterprise cloud environments: use Bedrock or Vertex AI

Rule of thumb

• Lowest ops: hosted API
• More flexibility, still low ops: managed endpoints
• Most control, more ops: self-hosting on Kubernetes/VMs/GPU instances

If you tell me:

1. your expected traffic,
2. whether you need open-source models,
3. and your budget/compliance constraints,

I can recommend a specific provider.