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OpenBookQA (HELM Lite, 5-shot multiple choice)

Science · 2023-12-19

HELM Lite's OpenbookQA run: the 500-question OpenBookQA test split posed five-shot as a single-letter multiple-choice question (HELM method multiple_choice_joint, temperature 0, one output token) and scored by exact match. Asked this way, capable models reach the mid-90s, while likelihood scoring of the same questions plateaus near 50%, so this protocol is its own factor group.

Top models (higher is better)

ModelScore
Claude 3.5 Sonnet (June 2024)97.2
GPT-4 Turbo97.0
GPT-4o (2024-08-06)96.8
Claude 3.5 Sonnet (Oct 2024)96.6
GPT-4o (2024-05-13)96.6
Qwen2.5 72B Instruct96.2
GPT-4 061396.0
Nova Pro96.0
Opus 395.6
DeepSeek-V395.4
Qwen2 72B Instruct95.4
Gemini 1.5 Pro 00295.2
GPT-4 Turbo (1106 Preview)95.0
Jamba 1.5 Large94.8
Gemini 2.0 Flash Experimental94.6
Llama 3.2 90B Vision Instruct94.2
Llama 3.1 405B Instruct94.0
Llama 3.1 70B Instruct93.8
Llama 3 70B93.4
Mistral Large 2 (Instruct 2407)93.2
Qwen1.5 32B93.2
Qwen1.5 72B93.0
Gemini 1.5 Flash 00192.8
Llama 3.3 70B Instruct92.8
Nova Lite92.8
Qwen1.5 110B Chat92.2
GPT-4o Mini92.0
Yi-34B92.0
Claude 3 Sonnet91.8
Gemma 2 27B IT91.8
Phi-3 Medium 4K Instruct91.6
Gemini 1.5 Flash 00291.4
Phi-3-Small-8K-Instruct91.2
DBRX Instruct91.0
Gemma 2 9B IT91.0
Claude 1.390.8
Gemini 1.5 Pro 00190.2
Mistral Large 1.089.4
Jamba 1.5 Mini89.0
Nova Micro88.8
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