2024 LLM Model Selection Guide: From GPT-4o to Claude 3.5 — How to Choose the Optimal AI Engine by Industry

2024 LLM releases: GPT-4o, Claude 3.5 Sonnet, and Llama 3

Historical scope: This article was first published on 31 May 2026 and looks back at models announced in 2024. Claude 3.5 Sonnet was announced in June 2024. This is neither a comparison written in 2024 nor a current model recommendation. Unsupported rankings and hypothetical industry success stories from the previous version have been removed. No API or performance tests were run for this revision.

For a current selection process, see the LLM model selection guide. Check model IDs, features, prices and retirement dates in each provider's current documentation before making a decision.

What the 2024 announcements establish

These are vendor announcements, not results of an independent test under shared conditions. They cannot justify a ranking for accuracy, cost or regulatory suitability. Self-hosting also incurs hardware, operations and security costs; it does not by itself establish compliance.

A repeatable selection method

1. Define the task and unacceptable errors, such as missed clauses, unsupported citations or disclosure of personal information.
2. Fix candidate model versions and record when you checked their current documentation, data terms and prices.
3. Use the same authorized representative inputs, prompts, output format and retry rules for every candidate.
4. Record accuracy, format compliance, latency, input and output tokens, and failure cases separately.
5. Estimate API cost as monthly calls × ((mean input tokens × input price per million) + (mean output tokens × output price per million)) / 1,000,000. Account for storage, retrieval and operations separately.
6. Keep model IDs in configuration. Re-evaluate before switching and define a rollback threshold for errors or latency.

Primary sources and limits

• OpenAI: GPT-4o announcement
• Anthropic: Claude 3.5 Sonnet announcement
• Meta: Llama 3 announcement

This is a review of announcements and an evaluation method. It does not verify industry fitness, certification, benchmark performance or cost advantage.