How much does a custom LLM or RAG app cost to build?
A custom RAG application over your own data typically costs in the tens of thousands to build. Fine-tuning a model adds cost above that, and training from scratch — rarely necessary — can run well into six figures. On top of the build, budget for ongoing usage, hosting and maintenance. Data quality, accuracy requirements and integration are the main cost drivers. Ranges are indicative; scope determines the real number.
Figures are broad market indications to help you budget, not quotes. Actual pricing varies by scope, data and agency.
The three approaches, and what they cost
RAG (retrieval-augmented generation)
Connects an existing model to your own documents at query time. The most common and cost-effective approach for business use cases. Build cost typically in the tens of thousands; easy to keep current.
Fine-tuning an existing model
Adjusts a base model's behaviour on your data. Adds cost above RAG and needs quality training data. Justified when you need consistent style, format or domain behaviour RAG alone can't give.
Training a model from scratch
Rarely the right call for most businesses — expensive (well into six figures), data-hungry, and usually unnecessary given strong base models. Reserve for genuinely specialised needs.
What drives the cost
Data volume and quality
Clean, well-structured data is cheaper to work with. Messy or unstructured data needs preparation, which is often a significant part of the build.
Accuracy and evaluation
Higher accuracy requirements mean more evaluation, guardrails and iteration — critical for anything customer- or compliance-facing.
Integration
Wiring the app into your systems, auth and workflows adds scope beyond the core model work.
Ongoing usage
Inference and vector-store costs scale with usage; a high-traffic app has meaningful running costs.
Start with RAG unless you have a reason not to
Most businesses over-estimate what they need. RAG covers the majority of use cases at the lowest cost and effort. The pricing model shapes how you pay, and the same logic applies to a chatbot build and AI projects in general.
Find an LLM/RAG specialist
NorthBridge AI connects you with verified agencies experienced in RAG and custom LLM applications, with escrow-protected milestone pricing. See how it works.
Frequently asked questions
How much does it cost to build a custom LLM or RAG application?
A retrieval-augmented generation (RAG) application over your own data commonly costs in the tens of thousands to build, depending on data volume, integration and accuracy requirements. Fine-tuning an existing model on your data adds cost above that, and training a model from scratch is rarely justified for most businesses and can run well into six figures. On top of the build, budget for ongoing model/API usage, hosting and maintenance. Ranges are indicative — scope drives the real figure.
Is RAG cheaper than fine-tuning or training a model?
Usually, yes. RAG connects an existing model to your data at query time, which is faster and cheaper to build and easier to keep up to date than fine-tuning. Fine-tuning changes the model's behaviour and costs more; training from scratch is the most expensive and rarely necessary. Most business use cases are best served by RAG, sometimes with light fine-tuning.
What are the ongoing costs of an LLM application?
Ongoing costs include model or API usage that scales with how much you use it, vector database and hosting costs, monitoring and evaluation to catch quality drift, and periodic updates as your data and requirements change. For a production system these running costs are a real part of the total cost of ownership, not an afterthought.
Build your LLM/RAG app with a verified agency
Compare vetted LLM and RAG specialists on NorthBridge AI.
Browse verified agencies