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Lesson 3 of 5 · 7 min read · Beginner

Scenarios 5 and 6: GPT-5.5 for classification and the researcher paying twice

A small business classifying 50,000 support messages a month on GPT-5.5, and a researcher paying for both Perplexity Pro and ChatGPT Plus. One is a 25× overpay; the other is two subscriptions for one search habit.

In this lesson you will

  • Price a high-volume, short-output job across three model sizes
  • See why output length, not model name, decides classification cost
  • Choose between two research subscriptions that overlap

Volume changes everything. At ten items a day, model choice is a rounding error. At 50,000 a month, the difference between the flagship and the small model is the difference between a real line on the accounts and a coffee.

Scenario 5: classification at scale on GPT-5.5

A small online retailer tags every incoming support message as *refund*, *delivery*, *product* or *other*. About 50,000 messages a month, each roughly 300 input tokens, with a one-word answer of about 10 output tokens. They set it up on GPT-5.5 ($5 in / $30 out per 1M) because it was the default in the dropdown.

Which would you trust?

Which is the cheapest model that still does this classification job?

Scenario 6: Perplexity Pro and ChatGPT Plus

Marcus, a market researcher, pays $20 for Perplexity Pro and $20 for ChatGPT Plus. What each is doing for him.
TaskPerplexity Pro $20ChatGPT Plus $20Overlap?
Web research with cited sourcesCore featureSearch is built inYes
Summarising uploaded reportsYesYesYes
Drafting the report itselfAdequateStrongMostly
Access to several vendors' modelsYes, in one placeOpenAI onlyNo
Monthly total$40 for one research workflow

Verdict: keep one. Both search the web with citations and both summarise uploads. If Marcus's day is mostly search-then-cite, Perplexity Pro at $20 does it and ChatGPT Free covers the occasional draft. If his day is mostly drafting with some search, ChatGPT Plus at $20 does it and Perplexity's free tier covers the occasional deep lookup. Either way the saving is $20 a month, $240 a year, and the only genuine reason to keep both is a task one of them cannot do, which the table does not show.

Lesson FAQ

What is the cheapest model for text classification?

The smallest tier that matches human labels on a sample. On the OpenAI ladder that is GPT-5.4 nano at $0.20 / $1.25 per 1M, about $3.63 for 50,000 short messages. DeepSeek V4 Flash at $0.05 / $0.16 is cheaper still where the hosting policy allows.

Why is GPT-5.5 so much more expensive for classification?

Because classification is input-heavy, and GPT-5.5's input rate is $5 per 1M against nano's $0.20: a 25× gap. The flagship's strengths are reasoning and open-ended generation, neither of which a four-way tag uses.

Should I pay for Perplexity Pro and ChatGPT Plus?

Rarely. Both do cited web search and both summarise uploads. Pick the one that matches most of your day and use the other's free tier for the rest. Two $20 research seats is a $240-a-year overlap unless one does something specific the other cannot.

How do I test whether a small model is accurate enough?

Take 200 real messages your team has already tagged, run them through the small model, and count matches. If it agrees with the humans as often as the flagship does, it passes. If not, try the next tier up before jumping to the top.

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