A new skill for Claude Code, named Autoprompt, has significantly improved the performance of the DeepSeek V4 Flash model on the Terminal-Bench 2.1 benchmark. This skill, which automates much of the coding loop by planning, building, testing, reviewing, and repairing code, pushed DeepSeek V4 Flash's score from 67.42% to 82.02%. While Autoprompt uses approximately double the tokens and triple the runtime, it is designed for complex tasks and aims to enhance work quality. AI
IMPACT This development suggests that advanced prompting techniques and code-generation workflows can significantly enhance the capabilities of existing LLMs.
RANK_REASON The cluster describes a new skill/workflow for an existing model, not a new model release from a frontier lab.
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