Tokenization Efficiency and Inference Latency in Romanized Nepali Across Llama-3.1, Mistral, and Qwen

Abstract

Abstract: This report synthesises findings from 3 peer-reviewed papers addressing the following research question: What is the correlation between tokenization efficiency and inference latency for Romanized Nepali tasks across Llama-3.1, Mistral, and Qwen architectures. Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains critically underresourced in the landscape of Large Language Models (LLMs). This study presents a systematic benchmarking of. 8 claims were extracted from source literature; 8 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

What is the correlation between tokenization efficiency and inference latency for Romanized Nepali tasks across Llama-3.1, Mistral, and Qwen architectures?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance