This is a structural limitation for any developer trying to use an LLM as a coding agent. The model applies the same playbook it knows, hits a wall, and stops making progress regardless of how long it runs. GLM-5.1, by contrast, is built to stay effective on agentic tasks over much longer horizons. The model handles ambiguous problems with better judgment and stays productive over longer sessions. It breaks complex problems down, runs experiments, reads results, and identifies blockers with real precision. By revisiting its reasoning and revising its strategy through repeated iteration, GLM-5.1 sustains optimization over hundreds of rounds and thousands of tool calls.
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