Accuracy on MMLU's jurisprudence questions, one of 57 subject tests of academic and professional knowledge.
unassessed
| Category | knowledge |
|---|---|
| Subcategory | Humanities |
| Page status | active |
| Metric | accuracy |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 108 |
| Dataset licence | MIT |
| Publisher | UC Berkeley |
Legal theory and the philosophy of law: schools of jurisprudence, sources of law, and the relationship between law and morality, rather than the law of any one jurisdiction. Framed as four-option multiple-choice questions and scored zero-shot or few-shot by exact match against the labelled option, as one of the 57 subject subsets that make up the MMLU benchmark.
Four-option multiple-choice question answering (A-D), one correct answer, zero-shot or few-shot.
| Model | Provider | Score | Card as of |
|---|---|---|---|
| Nous Hermes 2 Yi 34B | Nous Research | 89.8 | 2024-07 |
| Yi 1.5 34B 32K | 01.AI | 88.9 | 2024-07 |
| Yi 34B 200K | 01.AI | 88.9 | 2024-07 |
| Yi 34B Chat | 01.AI | 88.9 | 2024-07 |
| Meta Llama 3 70B | Meta | 88.0 | 2024-07 |
| Meta Llama 3 70B Instruct | Meta | 88.0 | 2026-04 |
| Meta Llama 3 70B Instruct | Nous Research | 88.0 | 2026-04 |
| Mixtral 8x22B Instruct v0.1 | Mistral AI | 86.1 | 2026-04 |
| Yi 1.5 34B | 01.AI | 85.2 | 2026-04 |
| Mixtral 8x7B Instruct v0.1 | Mistral AI | 84.3 | 2026-04 |
| Nous Hermes 2 Mixtral 8x7B DPO | Nous Research | 84.3 | 2024-07 |
| Mixtral 8x7B v0.1 | Mistral AI | 83.3 | 2026-04 |
| Yi 1.5 34B Chat | 01.AI | 83.3 | 2026-04 |
| Yi 1.5 34B Chat 16K | 01.AI | 83.3 | 2024-07 |
| Yi 1.5 9B 32K | 01.AI | 80.6 | 2024-07 |
| Claude Opus 4 | Anthropic | 80.5 | 2026-04 |
| Claude Opus 4.6 | Anthropic | 80.5 | 2026-04 |
| GPT-4.1 | OpenAI | 79.8 | 2026-04 |
| Phi 3 mini 4K instruct | Microsoft | 79.6 | 2024-07 |
| Yi 6B | 01.AI | 79.6 | 2024-07 |
| Yi 6B Chat | 01.AI | 79.6 | 2024-07 |
| Yi 9B | 01.AI | 79.6 | 2024-07 |
| Gemini 2.5 Pro | Google DeepMind | 79.2 | 2026-04 |
| Nous Hermes 2 SOLAR 10.7B | Nous Research | 78.7 | 2024-07 |
| GPT-4o | OpenAI | 78.5 | 2026-04 |
| GPT-4o (2024-05-13) | OpenAI | 78.5 | 2026-04 |
| GPT-4o (2024-08-06) | OpenAI | 78.5 | 2026-04 |
| GPT-4o (2024-11-20) | OpenAI | 78.5 | 2026-04 |
| GPT-4o mini | OpenAI | 78.5 | 2026-04 |
| Claude Sonnet 4 | Anthropic | 77.8 | 2026-04 |
| Claude Sonnet 4.5 | Anthropic | 77.8 | 2026-04 |
| Claude Sonnet 4.5 (latest) | Anthropic | 77.8 | 2026-04 |
| gemma 7B it | Google DeepMind | 77.8 | 2024-07 |
| Meta Llama 3 8B Instruct | Meta | 77.8 | 2024-07 |
| Meta Llama 3 8B Instruct | Nous Research | 77.8 | 2024-07 |
| Phi 3 mini 128K instruct | Microsoft | 77.8 | 2024-07 |
| Yi 1.5 6B | 01.AI | 77.8 | 2024-07 |
| Yi 1.5 6B Chat | 01.AI | 77.8 | 2024-07 |
| Yi 1.5 9B Chat 16K | 01.AI | 77.8 | 2024-07 |
| Hermes 2 Theta Llama 3 8B | Nous Research | 75.9 | 2024-07 |
| Meta Llama 3 8B | Meta | 75.0 | 2024-07 |
| Meta Llama 3 8B | Nous Research | 75.0 | 2024-07 |
| Yi 1.5 9B Chat | 01.AI | 75.0 | 2024-07 |
| DeepSeek R1 | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 0528 | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 0528 NVFP4 v2 | NVIDIA | 74.5 | 2026-04 |
| DeepSeek R1 0528 Qwen3 8B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Llama 70B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Llama 8B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Qwen 1.5B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Qwen 14B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Qwen 32B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek R1 Distill Qwen 7B | DeepSeek | 74.5 | 2026-04 |
| DeepSeek Reasoner | DeepSeek | 74.5 | 2026-04 |
| Mistral 7B Instruct v0.2 | Mistral AI | 74.1 | 2024-07 |
| Mistral 7B v0.3 | Mistral AI | 74.1 | 2024-07 |
| mistral 7B v0.3 bnb 4bit | Unsloth | 74.1 | 2024-07 |
| Yi 1.5 9B | 01.AI | 74.1 | 2024-07 |
| Qwen 3 235B Instruct | Cerebras | 73.8 | 2026-04 |
| Qwen3 235B-A22B | Alibaba / Qwen Team | 73.8 | 2026-04 |
| Hermes 2 Pro Llama 3 8B | Nous Research | 73.1 | 2024-07 |
| phi 2 | Microsoft | 73.1 | 2024-07 |
| Gemma 4 31B | Google DeepMind | 71.5 | 2026-04 |
| gemma 4 31B it | Google DeepMind | 71.5 | 2026-04 |
| gemma 4 31B it GGUF | Unsloth | 71.5 | 2026-04 |
| Gemma 4 31B IT NVFP4 | NVIDIA | 71.5 | 2026-04 |
| Mistral Large (latest) | Mistral AI | 71.2 | 2026-04 |
| Mistral Large 2.1 | Mistral AI | 71.2 | 2026-04 |
| Mistral Large 3 | Mistral AI | 71.2 | 2026-04 |
| Gemma 4 26B | Google DeepMind | 70.2 | 2026-04 |
| Llama 3.3 70B Instruct NVFP4 | NVIDIA | 69.5 | 2026-04 |
| Llama-3.3-70B-Instruct | Meta | 69.5 | 2026-04 |
| falcon 40B | TII | 69.4 | 2024-07 |
| Qwen2 1.5B Instruct | Alibaba / Qwen Team | 69.4 | 2024-07 |
| Llama 3.1 70B | Meta | 68.8 | 2026-04 |
| Llama 3.1 70B Instruct | Meta | 68.8 | 2026-04 |
| phi 4 | Microsoft | 66.8 | 2026-04 |
| Phi 4 mini instruct | Microsoft | 66.8 | 2026-04 |
| Phi 4 multimodal instruct | Microsoft | 66.8 | 2026-04 |
| deepseek llm 7B base | DeepSeek | 63.0 | 2024-07 |
| deepseek llm 7B chat | DeepSeek | 63.0 | 2024-07 |
| Qwen2 0.5B Instruct | Alibaba / Qwen Team | 59.3 | 2024-07 |
| chatglm2 6B | Zhipu AI | 58.3 | 2024-07 |
| gemma 2B it | Google DeepMind | 46.3 | 2024-07 |
| gemma 2B | Google DeepMind | 41.7 | 2024-07 |
| deepseek coder 6.7B instruct | DeepSeek | 37.0 | 2024-07 |
| deepseek coder 6.7B base | DeepSeek | 34.3 | 2024-07 |
| deepseek coder 1.3B base | DeepSeek | 25.0 | 2024-07 |
| deepseek coder 1.3B instruct | DeepSeek | 25.0 | 2024-07 |
| OLMo 1B hf | Allen AI | 24.1 | 2024-07 |