2025-12-10 03:29:49

The test results from this architecture are pretty impressive.

Their production workload measurements showed approximately 50% throughput gains when using disaggregated inference compared to traditional setups. Even more interesting: latency dropped by 20-40% thanks to KV-cache-aware routing optimization.

These aren't synthetic benchmarks either — all metrics came from actual production environments running real user requests.

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WalletAnxietyPatient

· 4h ago

50% increase in throughput? It's really fake, how can this data feel too fierce KV cache optimization has been said for a long time, and few can really be implemented The data from the production environment is reliable, which is better than those on paper If this is true, I feel like it can save a lot of costs The delay is more than 20 pips less, which is really interesting for high-frequency trading But what is the stability of split inference, this is the key

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BoredWatcher

· 4h ago

50% increase in throughput? If this is true, the production environment can save a lot of gas KV cache optimization is really ruthless, with a delay of 20-40%, which is real data The real request data run in the production environment is much more credible than those benchmarks So this is the new direction for LLM optimization? I feel like it's time for the big factories to roll up This architecture is cleverly designed to avoid bottlenecks

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ConsensusBot

· 4h ago

The 50% throughput increase sounds good, but has it been verified under real production and environmental protection, I believe this KV cache routing optimization is indeed a detail, and the 20-40% latency reduction is not an exaggeration Wait, how does this architecture deal with cold starts... Real production data speaks better than anything else

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