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Recursive Raises Mean SOL Score on Nvidia SOL-ExecBench to 0.754

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Cong Lu#1693
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Cong Lu@cong_ml#1693inTech

What’s exciting to me is not just any one result.

It’s that one system can make progress across problems with very different bottlenecks: model quality under a compute budget, wall-clock training speed, and hardware-level kernel performance.

Cong Lu@cong_ml

Domain 3: low-level GPU kernel optimization ⚙️

On Nvidia’s SOL-ExecBench, the same general system improved mean SOL score from 0.699 to 0.754 across 235 kernels - an 18% reduction in the gap to the theoretical optimum.

1:47 AM · Jun 11, 2026 · 151 Views
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Users are excited about Recursive advancing its mean SOL score on Nvidia SOL-ExecBench because the project's automated research loop searches ideas, turns them into executable changes, then tests and validates results.

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Cong Lu@cong_ml

The common thread is the automated research loop.

Search over ideas, turn them into executable changes, test them, validate + cross-check the result, and use empirical evidence to plan the next ideas.

Extremely excited to keep pushing @Recursive_SI !!

Cong Lu@cong_ml

What’s exciting to me is not just any one result.

It’s that one system can make progress across problems with very different bottlenecks: model quality under a compute budget, wall-clock training speed, and hardware-level kernel performance.

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