SWE-Bench Pro consists of 1865 tasks. https://arxiv.org/abs/2509.16941 Qwen3-Coder-Next solved 44.3% (826 or 827) of these tasks. To solve a single task, it took between ≈50 and ≈280 agent turns, ≈150 on average. In other words, a single pass through the dataset took ≈280000 agent turns. Kimi-K2.5 solved ≈84 fewer tasks, but also only took about a third as many agent turns.

Essentially the more turns you have the more the agent is likely to fail since the error compounds per turn. Agentic model are tuned for “long horizon tasks” ie being able to go many many turns on the same problem without failing.