MT-Bench
conversationalMT-Bench (Multi-Turn Benchmark) evaluates conversational ability through 80 carefully designed multi-turn questions across 8 categories including writing, roleplay, reasoning, math, coding, STEM, humanities, and extraction.
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Models Tested
0.0
Average Score
0–10
Scale Range
0.8x
Weight
How It Works
Models engage in two-turn conversations (question → response → follow-up → response). GPT-4 scores each turn on a scale of 1-10. The benchmark tests whether models can maintain coherence and quality across multiple exchanges.
Why It Matters
Real conversations are multi-turn, but most benchmarks only test single-turn responses. MT-Bench specifically evaluates the ability to build on previous context, handle follow-ups, and maintain consistency.
Limitations
Only 80 questions limits statistical power. GPT-4 judging introduces bias. Two turns is still relatively short compared to real conversations. The 1-10 scale makes most good models cluster around 8-9.