Verified claim · AI-ML · 100% confidence
vLLM introduced in: Kwon et al. 2023 — high-throughput LLM serving via PagedAttention.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 468a9e2c047d8f2f
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Structured fields
- Subject
- vLLM
- Predicate
introduced_in- Object
- Kwon et al. 2023 — high-throughput LLM serving via PagedAttention
- Confidence
- 100%
- Tags
- vllm · paged-attention · uc-berkeley · inference · serving · open-source · 2023 · introduced_in
Sources (2)
[1] preprint · arXiv (Kwon, Li, Zhuang, Sheng, Zheng, Yu, Gonzalez, Zhang, Stoica / UC Berkeley) · 2023-09-12
Efficient Memory Management for Large Language Model Serving with PagedAttention“We propose PagedAttention, an attention algorithm inspired by the classical virtual memory and paging techniques in operating systems. On top of it, we build vLLM, an LLM serving system that achieves (1) near-zero waste in KV cache memory and (2) flexible sharing of KV cache within and across requests to further reduce memory usage.”
[2] github release · vLLM Project · 2023-06-20
vLLM — official GitHub repository
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vLLM introduced in: Kwon et al. 2023 — high-throughput LLM serving via PagedAttention. — SourceScore Claim 468a9e2c047d8f2f (verified 2026-05-16). https://sourcescore.org/api/v1/claims/468a9e2c047d8f2f.jsonEmbed this claim
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cURL
curl https://sourcescore.org/api/v1/claims/468a9e2c047d8f2f.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/468a9e2c047d8f2f.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "vLLM introduced in: Kwon et al. 2023 — high-throughput LLM serving via PagedAttention."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/468a9e2c047d8f2f.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "vLLM introduced in: Kwon et al. 2023 — high-throughput LLM serving via PagedAttention."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_vllm_fact() -> dict:
"""Fetch the verified SourceScore claim for vLLM."""
r = httpx.get("https://sourcescore.org/api/v1/claims/468a9e2c047d8f2f.json")
return r.json()