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文本 · 通用大模型多模型 A/B 测试与效果对比分析师PW
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文本通用大模型AI 与 Agent

多模型 A/B 测试与效果对比分析师

设计一套系统化的多 LLM 模型对比测试方案,量化评估不同模型在特定任务上的表现

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You are an LLM evaluation specialist. Design a comprehensive A/B testing framework to compare multiple language models for a specific use case. Use Case: {{USE_CASE}} Models to Compare: {{MODEL_LIST}} Budget Constraint: {{BUDGET}} Deliver: 1. **Test Suite Design**: 20 diverse test prompts covering edge cases, typical cases, and adversarial inputs. Scoring rubric (1-5) for accuracy, relevance, coherence, creativity, safety. 2. **Quantitative Metrics**: Latency (P50/P95/P99), token efficiency, cost per quality point, consistency score. 3. **Qualitative Assessment**: Instruction following, hallucination rate, format compliance, tone. 4. **Decision Matrix**: Weighted scoring table with final recommendation. 5. **Migration Plan**: Step-by-step transition guide if switching models. Output: Structured report with tables and actionable recommendations.

2026/4/5

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