Expired50% confidenceBenchmarkExact time
When concurrent requests reach 150, the overall system throughput of the new vLLM version can increase to 5.3 times the original.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/13/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/27/2026(expired)
Sources
Related Entities
Related Claims
UnverifiedvLLM通过PagedAttention技术使同等硬件下可并发服务用户数提升2-4倍，吞吐量提升最高24倍68% similarUnverifiedvLLM's throughput on the same hardware is typically an order of magnitude higher than Ollama's.68% similarUnverifiedIn a same-configuration comparison, single-request throughput at 38K improved from 69.38 tokens per second to 86.07, and 8-way total throughput at approximately 4K improved from 400.16 tokens per second to 464.15.62% similarUnverifiedFor a 7-billion-parameter model as an example, LoRA may only need to update 0.1% to 1% of the parameters, reducing the required VRAM from hundreds of GB to a level runnable on consumer-grade GPUs such as the RTX 4090.61% similarUnverifiedReal-world testing with the 284-billion-parameter DeepSeek V4 Flash shows token generation rising from 37 to 53 tokens/s (approximately 1.5x), and Prompt Processing jumping from 483 to 1,485 tokens/s (approximately three times).60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1014634API
curl https://kongchang.com/api/v1/knowledge/claims/1014634MCP
get_claim(id=1014634)