Unverified50% confidenceFactExact time
现代语言模型的词汇表规模通常在32,000到100,000个token之间，使用BPE或SentencePiece等分词方法
1
Sources
50%
Confidence
Long-term
Relevance
8/28/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe vocabulary of a standard autoregressive language model typically contains 32,000 to 128,000 tokens.78% similarVerifiedThe context windows of current mainstream large language models range from tens of thousands to hundreds of thousands of tokens.72% similarUnverifiedGemma系列使用SentencePiece分词器，在BPE基础上引入Unigram语言模型，词表约含256,000个条目71% similarUnverifiedThe context window of large language models is limited, and the length of text that can be processed in a single inference is typically tens of thousands to hundreds of thousands of tokens.71% similarUnverified150,000 tokens correspond to approximately 100,000–120,000 English words of total input and output, which translates to roughly 3,000–5,000 lines of code plus a large volume of contextual dialogue and terminal interaction records.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/810543API
curl https://kongchang.com/api/v1/knowledge/claims/810543MCP
get_claim(id=810543)