Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures
Factual evidence
What the source reports
Research analyzes LLM inference nondeterminism across GPU architectures caused by floating-point non-associativity and reduction orders.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 23 September 2026
- Collected by OneBench
- 24 Sept 2026, 03:02 UK
Stored source excerpt
arXiv:2609.25624v1 Announce Type: cross Abstract: Large language model (LLM) outputs are expected to be reproducible under greedy decoding, yet in practice the same model, prompt,…
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OneBench interpretation
Institutional assessment
So what
Inconsistent outputs across GPU hardware complicate auditability and compliance testing for regulated production models.
Do what
Review model validation protocols with the team responsible for model risk to account for hardware-level inference variations.