Jev 在 agent 评测中对比 GPT-5.6 与 Sonnet 4.6
新评测称 Jev 500/500 二元决策与人类一致，方差比 GPT-5.6 Terra 低 913 倍，单次 0.44 秒、0.00035 美元。
Are you guys even paying attention? 913× lower score variance. That's what Jev recorded versus GPT-5.6 Terra in a new agent evaluation test. Jev was tested against GPT-5.6 Luna, Terra and Claude Sonnet 4.6 and delivered: → 500/500 binary decisions matched the human oracle → 92–913× lower variance → 0.44s average latency → $0.00035 per call Why it matters: Traditional code evals are rigid. LLM judges can be expensive, slow and inconsistent. Jev takes a different approach: structured decisions instead of generated text. That could make continuous, large-scale agent evaluation dramatically cheaper. The bigger unlock isn't just better agents. It's being able to test them constantly.
这条是引用着另一条写的：「LangChain 实测 Jev 对比 LLM 评审」