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Models update every few months. Knowing the version matters because behavior, price, and limits all change between releases.
AI labs ship new model versions constantly — Claude 3, 3.5, 4, 4.5, 4.7; GPT-4, 4o, 5, 5.1; Gemini 1.5, 2.0, 2.5. Each version has different strengths, prices, and quirks. APIs let you pin a version; chat apps usually default to the latest.
Check which model your favorite chat app currently uses (in settings). Note the version. Now you'll notice when it changes.
15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-models-model-versions-r8a8-teen
A developer pins their app to use 'gpt-4' in their API code. What will happen when OpenAI releases GPT-5?
What does it mean when an AI lab "deprecates" a model like gpt-3.5-turbo?
A student wrote code last year using Claude 3.5 Sonnet that worked perfectly. Now they're testing the same code with Claude 4.5, and some prompts produce different results. Why?
A chat app like ChatGPT or Claude AI typically defaults to which model version?
A developer wants their production app to always behave the same way for users. What should they do?
Why might upgrading from GPT-4 to GPT-5 save a developer money?
What should you do BEFORE judging whether an AI model is good or bad for your use case?
If you write a tutorial using Claude 4.5 today, what might happen to someone reading it six months later?
A company builds an app that relies on AI to summarize customer emails. They upgrade their model without re-testing their prompts. What could go wrong?
Why does knowing the specific model version matter for cost planning?
What does it mean that a model has "different strengths" between versions?
You notice your favorite AI chat app now behaves differently than last month. What's the most likely reason?
What should a developer do when their pinned model version is announced as deprecated?
What does the lesson suggest you do in your favorite chat app's settings?
A student says: 'I don't need to worry about model versions because AI always improves automatically.' What's wrong with this thinking?