How Much Does AI Cost Per Month?
When people ask, “How much does AI cost per month?” they’re not looking for vague ballpark numbers or tech fluff. They want straight answers:
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How much will it actually cost to run an AI app or service month after month?
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What do tools like GPT, Gemini, Claude, or open-source models charge you over time?
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Is AI affordable for startups or only realistic for big tech?
The problem is that most articles online throw around AI-generated estimates with no real context. They either oversimplify or overcomplicate things and rarely tell you what it really costs to build and operate an AI product at scale.
Here, I will try to give you a clear, use-case-based breakdown of monthly costs starting from quick experiments with open-source models to scaling real AI applications in production.
AI App Costs: What Are You Actually Paying For?
Before we start talking about numbers, I want you to understand what contributes to the monthly cost of running an AI application.
Here’s what makes up your bill, when you start to build an AI app:
|
Cost Component |
What It Covers |
|
Model or API usage |
Charges based on tokens, requests, or runtime |
|
Cloud compute |
Servers, GPUs, autoscaling, hosting AI endpoints |
|
Storage |
Vector databases, model weights, file storage, logs |
|
Inference costs |
Charges every time your app uses a model to generate a response |
|
APIs & 3rd party tools |
OCR, text to speech, image generation, analytics |
|
Development & maintenance |
Ongoing dev work, DevOps, model fine tuning, prompt optimization |
|
Security & monitoring |
Essential for production-level apps. Adds recurring costs |
The actual monthly cost depends on how you're deploying the AI:
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