Talaria: Session-Aware Serverless Serving of Hundred-Billion-Parameter LLMs
Serverless multi-model LLM systems multiplex popularity-skewed model catalogs over shared GPU pools, yet typically schedule each request independently. Tool-using agents break this abstraction: a session repeatedly calls an LLM across short tool gaps, carries a long reusable KV prefix, and is judged by session completion time (SCT). Load-only routing can separate a continuation from both its model and KV state, while round-based model multiplexing can delay even a correctly placed continuation until the target model's next slot. Both failures are especially costly for hundred-billion-parameter models: their weights constrain residency, while long-context KV is expensive to reconstruct or ...
| Authors | Utopia Meng, Unicornt Zhao, Derek Li et al. |
|---|---|
| Primary category | cs.DC |
| Published | 19 July 2026 |
| Last updated at source | 19 July 2026 |
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