Unverified50% confidenceFactExact time
On-device inference optimization and streaming processing technology allow the latency of real-time ASR to be kept within 200–500 milliseconds.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe end-to-end latency of a real-time AI tutor is composed of three stacked segments: ASR latency (50–500ms), LLM first-token generation latency (100–2000ms), and TTS first audio frame latency (50–300ms).77% similarUnverifiedIt is recommended to adjust the exception handling timeout of the large model node from the default 180 seconds to the platform maximum of 600 seconds, to avoid multimodal image input inference timeouts being incorrectly judged as failures.77% similarUnverifiedThe inference latency of the front-end lightweight model typically needs to be kept within 200 milliseconds to match the human perceptual threshold for real-time interaction.76% similarUnverifiedThe inference latency of dedicated safety classification models can be kept within 200–500 milliseconds, and can be compressed to the 100-millisecond range with quantization techniques and GPU inference optimization.76% similarUnverifiedStreaming output can reduce the user-perceived time-to-first-token from several seconds down to the millisecond level.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/894863API
curl https://kongchang.com/api/v1/knowledge/claims/894863MCP
get_claim(id=894863)