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New ESQ-Bench highlights Claude Sonnet 4.6's lead over GPT-4o in enterprise NL2SQL

By PulseAugur Editorial · [1 sources] ·

A new benchmark, ESQ-Bench, has been developed to evaluate Natural Language to SQL (NL2SQL) models on enterprise database environments, which are more complex than typical academic benchmarks. The benchmark includes six populated schemas and 550 question-query pairs across three complexity tiers, using Oracle as the primary database. Initial tests show that Claude Sonnet 4.6 outperforms GPT-4o on ESQ-Bench, particularly at higher complexity tiers, while open-weight models like Llama 3.2 struggle significantly. AI

IMPACT This benchmark could drive improvements in enterprise-grade NL2SQL capabilities, pushing models to better handle complex database schemas and dialects.

RANK_REASON The item describes a new academic benchmark for evaluating NL2SQL models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New ESQ-Bench highlights Claude Sonnet 4.6's lead over GPT-4o in enterprise NL2SQL

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The item describes a new academic benchmark for evaluating NL2SQL models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Sanjay Mishra, Divya Chukkapalli, Ganesh R. Naik ·

    ESQ-Bench: A Multi-Tier Enterprise Oracle Benchmark for Evaluating NL2SQL Dialect Generalization and Silent Semantic Divergence

    arXiv:2608.23569v1 Announce Type: new Abstract: State-of-the-art Natural Language to SQL (NL2SQL) models report execution accuracy exceeding 89 percent on established benchmarks such as Spider and BIRD. However, these benchmarks rely on simplified academic schemas and open-source…

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