GLM-5 Serving Parameter Tuning for OpenClaw: Single-Deployment MaaS Inference Optimization for Long-Context Agent Workloads
arXiv 2607.02518•893a297d3920e864d289fe2870d7f34883f01f3435ec2aaed0b7e37e8e946098
CUTLASSGLM-5GPU-kernelsH100KV-cacheKubernetesLLM-inferenceMixture-of-ExpertsOpenClawPEEKRepliCore','deterministic-simulation'StateFlowSwiGLU-fusionchunked-prefillcuBLASedge-computingevidence-horizonforensicsoperational-memorypipeline-parallelismschedulingserving-optimizationsingle-GPU-finetuningtelecom-fine-tuningtensor-parallelism
Paper metadata
- arXiv ID
- 2607.02518
- Version
- Not specified by this published record
- Category
- Computer Science — Distributed, Parallel, and Cluster Computing (cs.DC)
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Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- 893a297d3920e864d289fe2870d7f34883f01f3435ec2aaed0b7e37e8e946098
- Enrichment time
- 2026-07-07T08:52:20Z
- AI-assisted enrichment
- Yes
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