Unverified50% confidenceFactExact time
Flide uses compact pre-recorded execution graphs to accommodate diverse request mixes, meaning that requests with different tree structures can be mapped onto a small number of precompiled computation graphs for execution, thereby avoiding the overhead of dynamically building a computation graph for each request while maintaining low latency.
1
Sources
50%
Confidence
Long-term
Relevance
11/2/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedDynamic batching is a scheduling strategy for aggregating requests in inference services: the system maintains a request queue and, within an extremely short time window, packs multiple requests into a batch and sends it to the chip, amortizing the cost of a single forward computation and improving chip utilization.73% similarUnverifiedDynamic batching strategies collect requests within a short time window and execute inference immediately upon reaching the maximum batch size or a timeout threshold.70% similarUnverifiedChunked prefill splits a long prompt into chunks that are computed in batches, and the chunk size and scheduling depend on the load from other requests at that time, so the same long prompt takes different computation paths under different traffic.70% similarUnverifiedFluid compute lets multiple concurrent requests share the same instance and preserves the initialized runtime environment between requests, thereby reducing cold start overhead and improving resource utilization.69% similarUnverifiedStep-by-step follow-ups amount to breaking one large-scale reasoning task into multiple small reasoning chains, each of which gets a full context window and reasoning resources.69% similar
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