Thinking Machines' ReViSQL-K2.6 scores 91.37% on cleaned SQL benchmark

ReViSQL-K2.6 reached 88.55% with greedy decoding and 91.37% with 16-sample self-consistency on the corrected Arcwise-Plat-SQL benchmark.

By · Published

Primary source: Thinking Machines Newsroom

Why it matters

ReViSQL supports Murati's argument that specialized training can beat bigger models and intricate agent workflows, but it also exposes the bill: expert data cleanup and carefully designed rewards remain essential.

Vector illustration showing the ReViSQL-K2.6 model processing SQL data, with a benchmark chart showing its 92.97% score surpassing a human proxy's.

Mira Murati (@miramurati)'s Thinking Machines Lab and four academic researchers trained a single model to outperform elaborate text-to-SQL agent pipelines, after finding that errors riddled the benchmark data used to teach and judge those systems.…

Reader comments

Conversation for this story loads after sign-in.