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Prompt boundary inspection

GPT Tokenizer

What is a GPT tokenizer?

A GPT tokenizer converts text into the token IDs processed by GPT models. This page uses an o200k-compatible browser encoding to count and visualize text locally. The result is compatible for supported text, but complete API billing can also include message framing, tools, images, audio, cached input, and generated output.

Verified Last verified: Source: OpenAI model documentation OpenAI official API pricing
Compatible

Uses OpenAI's o200k-compatible text encoding locally. API message wrappers, tools, images, and provider-side changes can alter billed usage. Use the GPT tokenizer to see how text, punctuation, spaces, newlines, code, and message roles affect compatible token boundaries.

Processed in this browser
Token analysisDebounced local analysis
Total tokens0
Characters89
Words14
Estimated input cost$0.0000
CompatibleUses OpenAI's o200k-compatible text encoding locally. API message wrappers, tools, images, and provider-side changes can alter billed usage.
Context usage0.00% of 1,050,000
Token visualization
A guarded estimate is shown; individual token IDs are unavailable.

Provider API usage records remain the final source of truth for billing.

Official pricing evidence

GPT tokenizer: GPT-5.6 Terra standard text rates

Input $2, cached input $0.2, and output $12 per 1M tokens.

Checked OpenAI official API pricing GPT-5.6 Terra model documentation

This GPT tokenizer uses these rates for the selected text scenario. Standard direct OpenAI API text rates. Requests above 272K input tokens use 2x input and cached-input rates and 1.5x output rates for the full request.

What does a GPT tokenizer count?

A GPT tokenizer does not simply count words. It maps text into vocabulary IDs that may represent a word, part of a word, punctuation, leading whitespace, or a byte sequence. The color blocks above make those boundaries inspectable without sending the prompt away.

Turn on Show whitespace when two prompts look identical but produce different counts. Turn on Show token IDs when you are comparing serialization or building a repeatable prompt test. The GPT tokenizer keeps those controls secondary until you need them.

Does a GPT token count include the whole API request?

A production prompt often includes a system instruction, examples, conversation history, tool definitions, and the next user request. Chat mode lets the GPT tokenizer separate message content before adding a visible format estimate.

This distinction matters near a context limit. The GPT tokenizer can show that visible text fits, but tool schemas and expected output still need room. Budget context for the complete request plus the response, not only the pasted paragraph.

When should you inspect GPT token IDs?

Token IDs are useful when a delimiter, product code, URL, or unusual spelling breaks into many pieces. They are not a quality score. A low ID or a visually short token does not mean the model understands it better.

For very large input, the GPT tokenizer avoids rendering every token span. It keeps the total and shows a guarded preview, preventing the visualization itself from becoming the browser bottleneck.

How much does a GPT prompt cost?

Prompt cost depends on the selected GPT model, normal input tokens, eligible cached input, and any generated output. The GPT tokenizer estimates the visible input first; the GPT API cost calculator then applies the current per-million rates from OpenAI's linked pricing page.

Use the GPT tokenizer as the visible-text baseline. Message framing, tools, media, retries, and output can make the complete provider charge higher than the pasted-text estimate.

Source and method

Which OpenAI official source and measured checks support this GPT tokenizer?

The browser loads the o200k_base encoding and counts the entire submitted text before creating a limited visual preview. OpenAI's token guide establishes that tokens may be words, fragments, punctuation, or spaces. The measured count is compatible text evidence. Its limitation is that it excludes hidden API framing, tools, media, generated output, and an invoice. OpenAI official model documentation. Last verified: .

Which OpenAI official source and measured checks support this GPT tokenizer? Evidence and limitations for the current page.
EvidenceObserved result or boundary
Local counting methodFull input encoded with o200k_base; only the first and last token pieces are rendered for very large results.
Accuracy boundaryCompatible for supported text, not a complete OpenAI API billing record.
Answers

GPT Tokenizer questions

What encoding does the GPT tokenizer use?

It dynamically loads o200k_base, an OpenAI-compatible text encoding used here for local planning.

Can I copy token IDs?

Yes. The GPT tokenizer Copy Token IDs action copies the IDs currently represented in the visualization. Very large inputs use a limited first-and-last preview.

Why does whitespace change GPT tokens?

Vocabulary entries often include leading spaces or common text fragments, so changing spaces or newlines can change token boundaries.

Is this the same as ChatGPT billing?

No. The GPT tokenizer counts compatible text. Complete ChatGPT product or API accounting can include additional request and output data.

Use this result for planning, not as a billing record

This GPT tokenizer is suitable for local text and budget planning, but it is not for provider invoicing. Use the GPT tokenizer to debug prompt structure; use an actual API usage response when a billable total or hard production limit must be exact. Provider API usage records remain the final source of truth for billing.