Unverified50% confidenceTradeoffExact time
High aggregate throughput often comes at the cost of larger batch sizes, and large batches drive up the time-to-first-token (TTFT) latency for individual requests.
1
Sources
50%
Confidence
Long-term
Relevance
9/24/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPursuing extreme throughput often comes at the cost of per-request latency, as throughput and latency metrics constrain each other.75% similarUnverifiedIncreasing batch size to improve throughput typically sacrifices per-request latency71% similarVerifiedThe KV cache VRAM usage of ultra-long context windows grows linearly with context length, causing inference latency and costs to rise significantly.70% similarUnverifiedModern large model inference typically uses batching technology to improve GPU utilization, and backlogs in the batching queue during peak periods cause the time to first token (TTFT) to become longer.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/947009API
curl https://kongchang.com/api/v1/knowledge/claims/947009MCP
get_claim(id=947009)