Intology's Locus agent beats Qwen3's human-tuned model

Intology's coding agent Locus post-trained a Qwen3 base model past Qwen3's own official Instruct checkpoint, per the company's blog.

On the actual PostTrainBench task, one H100 GPU and 10 hours across seven benchmarks, Locus scored 44.7%. The 51.6% figure that beats the official Qwen3-1.7B-Instruct model came from a different test. Intology built an expanded version of PostTrainBench itself, running thousands of H100 hours instead of one.

Intology calls this variant PostTrainBench+. It's the company's own extension of a third-party benchmark, not an entry on any external leaderboard. The blog post flags this directly: the headline comparison isn't apples to apples with how PostTrainBench was designed to be run.

The real number

Watch the 44.7%, not the 51.6%. That's Locus's score under the constraint the benchmark actually enforces: one H100, ten hours. It's the number that means something if another agent tries the same task on the same budget. The 51.6% only proves that more compute helps, which nobody needed an AI agent to demonstrate.