Cheapest way to host a model API

The cheapest way to host a model API depends on how much traffic you expect and whether you need real-time responses. In most cases, the cheapest options are:

1) Cheapest overall: Use a serverless / pay-per-use model API

If your traffic is low or spiky, don’t host the model yourself.

Options:

• OpenAI / Anthropic / Gemini APIs
• Hugging Face Inference Endpoints (managed, not always cheapest but easy)
• Together / Fireworks / Replicate / Groq for hosted open models

Why cheapest:

• No GPU server running 24/7
• No DevOps
• Pay only for usage

Best for:

• Prototypes
• Low traffic apps
• Apps where latency is okay and you want zero ops

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2) Cheapest self-hosted: small CPU server + small quantized model

If you must self-host, use a quantized small model on a cheap CPU VM.

Typical setup:

• llama.cpp, Ollama, or vLLM if GPU is available
• A 2–4 vCPU / 4–8 GB RAM VPS for small models
• Quantized models like:
  • Llama 3.2 1B/3B
  • Phi-3 mini
  • Gemma 2 2B
  • Mistral 7B quantized (may be tight on CPU)

Cheap providers:

• Hetzner
• OVH
• DigitalOcean (easy, but not always the cheapest)
• Vultr
• Hetzner CX instances are often among the best value

Why this can be cheap:

• Flat monthly cost
• Good for low request volume
• Works without GPU for smaller models

Tradeoff:

• Slower inference
• Limited model size
• Less concurrency

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3) Cheapest for bursty traffic: autoscaling GPU on demand

If you need faster responses or larger models, use temporary GPU instances only when needed.

Options:

• RunPod
• Modal
• Beam
• Lambda Labs
• Replicate (managed, convenient)
• AWS/GCP/Azure spot instances if you can handle interruptions

Why cheap:

• Spin up only when needed
• Use spot/preemptible GPUs
• Scale to zero when idle

Best for:

• Medium traffic
• Occasional heavy jobs
• Batch inference

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What is usually the absolute cheapest?

If you have very low traffic:

Use an external API like OpenAI/Groq/Together.
This is often cheaper than running a server 24/7.

If you want self-hosting and tiny costs:

Use a CPU VPS with a small quantized model.

If you need GPU performance:

Use spot/on-demand GPU only when active.

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Practical recommendation

If your goal is “lowest cost for a real product”:

• Start with a hosted API
• If cost grows, move to self-hosted open model
• Use small quantized models first
• Only move to GPU if latency/quality requires it

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Cheapest stack by scenario

A. Prototype / MVP

• OpenAI or Groq API
• Fastest to launch
• No infra cost

B. Tiny budget, self-hosted

• Hetzner VPS
• Ollama / llama.cpp
• Small quantized model

C. Need better quality + low ops

• RunPod or Modal
• GPU on demand
• Scale to zero

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Rule of thumb

• Under a few thousand requests/day: external API is often cheapest
• Consistent traffic with small models: CPU VPS may win
• Larger models or high concurrency: GPU hosting is necessary

If you want, I can give you:

1. the cheapest stack for your exact model, or
2. a cost comparison table for OpenAI vs self-hosted vs GPU providers.