Poolside's small open-weight coding model beats larger rivals on benchmarks

Poolside released Laguna S 2.1, its third coding model in three months, trained to check its own work and revise failed approaches during long agentic sessions rather than relying on raw scale. The compact model reportedly beats several much larger rivals on benchmarks, and Poolside says it solved a math problem open since 1975 for under 10 cents.

Why it matters: This continues a trend of smaller, cheaper open-weight models closing the gap with frontier-scale models by optimizing for self-correction rather than parameter count, which matters for anyone weighing inference cost against capability in coding agents.