What it is
OpenAI’s tokenizer documentation explains how language models process text using tokens; features include a token counter, character count, and a tokenization tool. It highlights that one token generally corresponds to about 4 characters or 3⁄4 of a word,…
Gabriel’s notes
Quick take: OpenAI’s tokenizer documentation explains how language models process text using tokens; features include a token counter, character count, and a tokenization tool. It highlights that one token generally corresponds to about 4 characters or 3⁄4 of a word,…
I saved this under Dev & code because it can help you build, test, or ship software faster (APIs, dev tooling, code assistance).
Good fit if you want to:
- build, test, or ship software faster (APIs, dev tooling, code assistance).
- work specifically with OpenAI models, docs, tooling, or ecosystem resources.
Pricing snapshot (auto-enriched): Free tier available; usage-based pricing per million tokens for input and output; no per-seat pricing; additional costs apply for built-in tools and web search tool calls.
Work-use / compliance snapshot (auto-enriched): OpenAI’s API platform, including the Tokenizer tool, is suitable for workplace use with strong data ownership and control, no default model training on customer data, configurable data retention policies including zero retention, enterprise-grade security with SOC 2 Type 2 compliance, HIPAA support via BAA, GDPR compliance, and availability of SAML SSO and fine-grained access controls.
Alternatives (auto-enriched): Alternative: TokenDagger | Comparison: TokenDagger is a faster drop-in replacement for OpenAI’s Tiktoken tokenizer, offering improved performance while maintaining compatibility.
Note: pricing and policy details can change—verify on the official site before making decisions.