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AI API Use Cases: Find the Right Model (2026)

Every AI workload has a different token profile — and the right model depends on your specific input/output ratio, volume, latency requirements, and quality threshold. Browse 8 use case guides below to find cost-effective model recommendations tailored to your workload.

All Use Case Guides

Customer Support Bot

AI-powered customer support chatbots handle common inquiries, route escalations, and provide 24/7 assistance. These workloads typically involve short-to-medium user messages and moderately detailed responses from a knowledge base.

10 recommended models
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Code Generation

Code generation workloads involve large prompts containing existing code context and detailed instructions, with lengthy generated code responses. These tasks benefit from models with strong coding benchmarks and large context windows.

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Content & Copywriting

Content and copywriting tasks involve brief prompts or outlines as input, with long-form generated content as output. Blog posts, marketing copy, and product descriptions are common examples where output tokens dominate costs.

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Data Extraction

Data extraction involves sending large documents or structured data as input and receiving concise structured output (JSON, CSV, key-value pairs). Input costs dominate due to long context and short structured responses.

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RAG / Semantic Search

Retrieval-Augmented Generation (RAG) pipelines retrieve relevant document chunks and include them with user queries. Input costs are driven by retrieved context, with moderate-length generated responses.

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Document Summarization

Document summarization processes long documents — contracts, research papers, reports, transcripts — and produces concise summaries. Dominated by high input token counts with moderate output length.

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General Chatbot

General-purpose conversational AI for consumer and enterprise applications. Balanced input and output token usage with conversational back-and-forth requiring context retention across turns.

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Text Classification

Text classification tasks involve short-to-medium input text and very brief output (a category label, sentiment score, or JSON object). Extremely cost-efficient at scale — ideal for high-volume automated pipelines.

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How Use Case Guides Work

Each use case guide profiles a specific AI workload — customer support bots, code generation, document summarization, content creation, and more — and provides tailored model recommendations based on the typical token profile for that workload.

Recommendations are ranked by cost-effectiveness at the use case's typical input/output token ratio. Each guide includes a volume cost table showing estimated monthly costs at low, medium, and high request volumes, plus optimization tips specific to that workload.

Use our interactive calculator to enter your exact token usage and see a real-time cost comparison across all supported models. Or browse provider pricing pages to compare all models from a single provider.

Compare by Provider

Already know which provider you want to use? Browse provider pricing pages to see all models, token costs, and capabilities in one place.