{
 "body": "\nPart of the [MMLU](mmlu.md) family.\n\n## What it measures\n\nCase-style problems in financial accounting, auditing, cost accounting, tax and business law,\nmixing numeric calculation (ratios, cost allocations, inventory valuation) with rule application\n(audit risk, revenue recognition, contract formation). Like the rest of MMLU, each question gives\nfour labelled options and the model is graded on picking the single correct one, typically\nevaluated 5-shot. The benchmark's own categorisation places this subject in the \"other\"\nsubcategory, within the \"other\" group of MMLU's four broad areas (STEM, humanities, social\nsciences, and other), alongside subjects such as anatomy and clinical knowledge.\n\n## Reading the numbers\n\nThe Hugging Face mirror holds 282 test questions (scored), plus 31 validation and 5 dev questions\nfor few-shot prompting. With well under a thousand items, a handful of questions can shift the\nreported percentage by a point or two, so treat small differences between models here as noisy\nrather than meaningful. A high score means the model applies accounting and auditing rules and\ncomputations correctly under exam phrasing; it does not show that the model can prepare or review\nan actual set of financial statements. Read it against a model's overall MMLU score and other\nsubjects in the \"other\" group, and see the [MMLU](mmlu.md) family page for the shared scoring\nprotocol, saturation and contamination notes that apply here too.\n",
 "build": {
  "built_at": "2026-09-09T16:56:50+00:00",
  "commit": "0a599558854c0e238c03a0f0d725239cb28f9d11",
  "eligibility_as_of": "2026-09-09"
 },
 "disposition": {
  "canonical_id": "mmlu_professional_accounting",
  "reasons": [],
  "status": "unassessed",
  "verified_results": []
 },
 "models_covered": [
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Claude Opus 4",
   "model_id": "anthropic/claude-opus-4-20250514",
   "provider": "anthropic",
   "provider_display": "Anthropic",
   "score": 72.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Claude Opus 4.6",
   "model_id": "anthropic/claude-opus-4-6",
   "provider": "anthropic",
   "provider_display": "Anthropic",
   "score": 72.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, anthropic-system-card-mythos"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4.1",
   "model_id": "openai/gpt-4-1",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 71.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, domain-evals preference-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Gemini 2.5 Pro",
   "model_id": "google/gemini-2-5-pro",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 71.2,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4o",
   "model_id": "openai/gpt-4o",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 70.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4o (2024-05-13)",
   "model_id": "openai/gpt-4o-2024-05-13",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 70.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4o (2024-08-06)",
   "model_id": "openai/gpt-4o-2024-08-06",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 70.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4o (2024-11-20)",
   "model_id": "openai/gpt-4o-2024-11-20",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 70.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "GPT-4o mini",
   "model_id": "openai/gpt-4o-mini",
   "provider": "openai",
   "provider_display": "OpenAI",
   "score": 70.5,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, domain-evals, llm-stats, intlpull"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Claude Sonnet 4",
   "model_id": "anthropic/claude-sonnet-4-20250514",
   "provider": "anthropic",
   "provider_display": "Anthropic",
   "score": 69.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Claude Sonnet 4.5",
   "model_id": "anthropic/claude-sonnet-4-5-20250929",
   "provider": "anthropic",
   "provider_display": "Anthropic",
   "score": 69.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Claude Sonnet 4.5 (latest)",
   "model_id": "anthropic/claude-sonnet-4-5",
   "provider": "anthropic",
   "provider_display": "Anthropic",
   "score": 69.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1",
   "model_id": "deepseek/deepseek-r1",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2, domain-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 0528",
   "model_id": "deepseek/deepseek-r1-0528",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2, domain-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 0528 NVFP4 v2",
   "model_id": "nvidia/deepseek-r1-0528-nvfp4-v2",
   "provider": "nvidia",
   "provider_display": "NVIDIA",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 0528 Qwen3 8B",
   "model_id": "deepseek/deepseek-r1-0528-qwen3-8b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "bigcode-leaderboard, provider-reports, open-llm-leaderboard"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Llama 70B",
   "model_id": "deepseek/deepseek-r1-distill-llama-70b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Llama 8B",
   "model_id": "deepseek/deepseek-r1-distill-llama-8b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Qwen 1.5B",
   "model_id": "deepseek/deepseek-r1-distill-qwen-1-5b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "bigcode-leaderboard, provider-reports, open-llm-leaderboard, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Qwen 14B",
   "model_id": "deepseek/deepseek-r1-distill-qwen-14b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Qwen 32B",
   "model_id": "deepseek/deepseek-r1-distill-qwen-32b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek R1 Distill Qwen 7B",
   "model_id": "deepseek/deepseek-r1-distill-qwen-7b",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "DeepSeek Reasoner",
   "model_id": "deepseek/deepseek-reasoner",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 68.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2, llm-stats"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Qwen 3 235B Instruct",
   "model_id": "cerebras/qwen-3-235b-a22b-instruct-2507",
   "provider": "cerebras",
   "provider_display": "Cerebras",
   "score": 67.5,
   "source": "bigcode-leaderboard, provider-reports, preference-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Qwen3 235B-A22B",
   "model_id": "qwen/qwen3-235b-a22b",
   "provider": "qwen",
   "provider_display": "Alibaba / Qwen Team",
   "score": 67.5,
   "source": "lmarena.ai, provider-reports, preference-evals, llm-stats, domain-evals"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mixtral 8x22B Instruct v0.1",
   "model_id": "mistral/mixtral-8x22b-instruct-v0-1",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 66.3,
   "source": "open-llm-leaderboard-v2, llm-stats, open-llm-leaderboard-v1"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mistral Large (latest)",
   "model_id": "mistral/mistral-large-latest",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 65.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, open-llm-leaderboard-v2, llm-stats"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mistral Large 2.1",
   "model_id": "mistral/mistral-large-2411",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 65.8,
   "source": "lmarena.ai, provider-reports, safety-evals, preference-evals,, domain-evals open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mistral Large 3",
   "model_id": "mistral/mistral-large-2512",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 65.8,
   "source": "lmarena.ai, provider-reports, multimodal-evals, safety-evals, preference-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Gemma 4 31B",
   "model_id": "google/gemma-4-31b",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 65.2,
   "source": "lmarena.ai, provider-reports, multimodal-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "gemma 4 31B it",
   "model_id": "google/gemma-4-31b-it",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 65.2,
   "source": "lmarena.ai, provider-reports, multimodal-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "gemma 4 31B it GGUF",
   "model_id": "unsloth/gemma-4-31b-it-gguf",
   "provider": "unsloth",
   "provider_display": "Unsloth",
   "score": 65.2,
   "source": "lmarena.ai, provider-reports, multimodal-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Gemma 4 31B IT NVFP4",
   "model_id": "nvidia/gemma-4-31b-it-nvfp4",
   "provider": "nvidia",
   "provider_display": "NVIDIA",
   "score": 65.2,
   "source": "lmarena.ai, provider-reports, multimodal-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Nous Hermes 2 Yi 34B",
   "model_id": "nous-research/nous-hermes-2-yi-34b",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 64.9,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Gemma 4 26B",
   "model_id": "google/gemma-4-26b",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 64.5,
   "source": "lmarena.ai, provider-reports, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 34B 32K",
   "model_id": "01-ai/yi-1-5-34b-32k",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 64.2,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Llama 3.3 70B Instruct NVFP4",
   "model_id": "nvidia/llama-3-3-70b-instruct-nvfp4",
   "provider": "nvidia",
   "provider_display": "NVIDIA",
   "score": 63.8,
   "source": "lmarena.ai, provider-reports, safety-evals, preference-evals, open-llm-leaderboard-v2, llm-stats"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Llama-3.3-70B-Instruct",
   "model_id": "meta/llama-3-3-70b-instruct",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 63.8,
   "source": "lmarena.ai, provider-reports, safety-evals, preference-evals, open-llm-leaderboard-v2, llm-stats"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 70B",
   "model_id": "meta/meta-llama-3-70b",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 63.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 70B Instruct",
   "model_id": "meta/meta-llama-3-70b-instruct",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 63.8,
   "source": "llm-stats, open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 70B Instruct",
   "model_id": "nous-research/meta-llama-3-70b-instruct",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 63.8,
   "source": "llm-stats, open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 34B Chat",
   "model_id": "01-ai/yi-1-5-34b-chat",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 63.1,
   "source": "open-llm-leaderboard-v2, open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 34B Chat 16K",
   "model_id": "01-ai/yi-1-5-34b-chat-16k",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 63.1,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Llama 3.1 70B",
   "model_id": "meta/llama-3-1-70b",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 62.5,
   "source": "lmarena.ai, provider-reports, safety-evals, domain-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Llama 3.1 70B Instruct",
   "model_id": "meta/llama-3-1-70b-instruct",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 62.5,
   "source": "lmarena.ai, provider-reports, safety-evals, domain-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 34B",
   "model_id": "01-ai/yi-1-5-34b",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 62.1,
   "source": "open-llm-leaderboard-v2, open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 34B Chat",
   "model_id": "01-ai/yi-34b-chat",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 61.7,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 34B 200K",
   "model_id": "01-ai/yi-34b-200k",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 61.3,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "phi 4",
   "model_id": "microsoft/phi-4",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 61.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2,, domain-evals llm-stats"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Phi 4 mini instruct",
   "model_id": "microsoft/phi-4-mini-instruct",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 61.2,
   "source": "lmarena.ai, provider-reports, preference-evals, llm-stats, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Phi 4 multimodal instruct",
   "model_id": "microsoft/phi-4-multimodal-instruct",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 61.2,
   "source": "lmarena.ai, provider-reports, preference-evals, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Phi 3 mini 128K instruct",
   "model_id": "microsoft/phi-3-mini-128k-instruct",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 58.5,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Phi 3 mini 4K instruct",
   "model_id": "microsoft/phi-3-mini-4k-instruct",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 58.2,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 9B Chat",
   "model_id": "01-ai/yi-1-5-9b-chat",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 57.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 9B Chat 16K",
   "model_id": "01-ai/yi-1-5-9b-chat-16k",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 57.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 9B",
   "model_id": "01-ai/yi-1-5-9b",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 56.7,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 9B 32K",
   "model_id": "01-ai/yi-1-5-9b-32k",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 56.7,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 9B",
   "model_id": "01-ai/yi-9b",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 56.4,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mixtral 8x7B Instruct v0.1",
   "model_id": "mistral/mixtral-8x7b-instruct-v0-1",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 55.3,
   "source": "open-llm-leaderboard-v2, open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 6B",
   "model_id": "01-ai/yi-1-5-6b",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 54.3,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 8B Instruct",
   "model_id": "meta/meta-llama-3-8b-instruct",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 52.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 8B Instruct",
   "model_id": "nous-research/meta-llama-3-8b-instruct",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 52.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Nous Hermes 2 Mixtral 8x7B DPO",
   "model_id": "nous-research/nous-hermes-2-mixtral-8x7b-dpo",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 52.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Hermes 2 Theta Llama 3 8B",
   "model_id": "nous-research/hermes-2-theta-llama-3-8b",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 52.1,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 1.5 6B Chat",
   "model_id": "01-ai/yi-1-5-6b-chat",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 52.1,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2026-04",
   "attribution": "unverified-legacy",
   "display_name": "Mixtral 8x7B v0.1",
   "model_id": "mistral/mixtral-8x7b-v0-1",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 51.8,
   "source": "open-llm-leaderboard-v2, open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Nous Hermes 2 SOLAR 10.7B",
   "model_id": "nous-research/nous-hermes-2-solar-10-7b",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 51.8,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Mistral 7B v0.3",
   "model_id": "mistral/mistral-7b-v0-3",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 51.1,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "mistral 7B v0.3 bnb 4bit",
   "model_id": "unsloth/mistral-7b-v0-3-bnb-4bit",
   "provider": "unsloth",
   "provider_display": "Unsloth",
   "score": 51.1,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Hermes 2 Pro Llama 3 8B",
   "model_id": "nous-research/hermes-2-pro-llama-3-8b",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 50.7,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "gemma 7B it",
   "model_id": "google/gemma-7b-it",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 49.3,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 8B",
   "model_id": "meta/meta-llama-3-8b",
   "provider": "meta",
   "provider_display": "Meta",
   "score": 49.3,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Meta Llama 3 8B",
   "model_id": "nous-research/meta-llama-3-8b",
   "provider": "nous-research",
   "provider_display": "Nous Research",
   "score": 49.3,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 6B",
   "model_id": "01-ai/yi-6b",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 47.9,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Yi 6B Chat",
   "model_id": "01-ai/yi-6b-chat",
   "provider": "01-ai",
   "provider_display": "01.AI",
   "score": 47.9,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Mistral 7B Instruct v0.2",
   "model_id": "mistral/mistral-7b-instruct-v0-2",
   "provider": "mistral",
   "provider_display": "Mistral AI",
   "score": 45.0,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "phi 2",
   "model_id": "microsoft/phi-2",
   "provider": "microsoft",
   "provider_display": "Microsoft",
   "score": 44.0,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "falcon 40B",
   "model_id": "tii/falcon-40b",
   "provider": "tii",
   "provider_display": "TII",
   "score": 43.6,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Qwen2 1.5B Instruct",
   "model_id": "qwen/qwen2-1-5b-instruct",
   "provider": "qwen",
   "provider_display": "Alibaba / Qwen Team",
   "score": 43.6,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "Qwen2 0.5B Instruct",
   "model_id": "qwen/qwen2-0-5b-instruct",
   "provider": "qwen",
   "provider_display": "Alibaba / Qwen Team",
   "score": 37.2,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek llm 7B base",
   "model_id": "deepseek/deepseek-llm-7b-base",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 36.5,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek llm 7B chat",
   "model_id": "deepseek/deepseek-llm-7b-chat",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 36.5,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek coder 6.7B base",
   "model_id": "deepseek/deepseek-coder-6-7b-base",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 34.8,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "gemma 2B",
   "model_id": "google/gemma-2b",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 34.0,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "chatglm2 6B",
   "model_id": "zhipu/chatglm2-6b",
   "provider": "zhipu",
   "provider_display": "Zhipu AI",
   "score": 33.3,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek coder 6.7B instruct",
   "model_id": "deepseek/deepseek-coder-6-7b-instruct",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 31.9,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "gemma 2B it",
   "model_id": "google/gemma-2b-it",
   "provider": "google",
   "provider_display": "Google DeepMind",
   "score": 30.5,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek coder 1.3B base",
   "model_id": "deepseek/deepseek-coder-1-3b-base",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 24.5,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "deepseek coder 1.3B instruct",
   "model_id": "deepseek/deepseek-coder-1-3b-instruct",
   "provider": "deepseek",
   "provider_display": "DeepSeek",
   "score": 24.5,
   "source": "open-llm-leaderboard-v1"
  },
  {
   "as_of": "2024-07",
   "attribution": "unverified-legacy",
   "display_name": "OLMo 1B hf",
   "model_id": "allen-ai/olmo-1b-hf",
   "provider": "allen-ai",
   "provider_display": "Allen AI",
   "score": 22.0,
   "source": "open-llm-leaderboard-v1, open-llm-leaderboard-v2"
  }
 ],
 "page": {
  "category": "knowledge",
  "dataset": {
   "languages": [
    "en"
   ],
   "license": "MIT",
   "modalities": [
    "text"
   ],
   "public_test_set": true,
   "size": 282,
   "size_note": "282 test questions (used for scoring), plus 31 validation and 5 dev (few-shot prompt) questions, per the Hugging Face parquet mirror of cais/mmlu, config 'professional_accounting'.",
   "splits": "dev (5), validation (31), test (282)",
   "url": "https://huggingface.co/datasets/cais/mmlu"
  },
  "freshness": {
   "researched": "2026-09-08",
   "researched_by": "sonnet-5 agent, batch 1b, slice N"
  },
  "harness": {
   "helm": "mmlu:subject=professional_accounting",
   "lm_eval": "mmlu_professional_accounting",
   "other": "hendrycksTest-professional_accounting in the pre-2024 Open LLM Leaderboard v1 harness fork"
  },
  "id": "mmlu_professional_accounting",
  "leaderboard_url": "https://github.com/hendrycks/test",
  "lineage": {
   "family": "mmlu"
  },
  "measures": "Case-style problems in financial accounting, auditing, cost accounting, tax and business law, mixing numeric calculation with rule application. Questions are four-option multiple-choice, drawn from the MMLU test set's \"other\" subcategory within the benchmark's \"other\" top-level group, and are graded on the single correct labelled option.",
  "metric": {
   "baseline_note": "25% is the four-option random-guess rate. No subject-specific human baseline is given by the paper for this subject; see the mmlu family page for the benchmark-wide human baselines.",
   "direction": "higher_is_better",
   "max_score": 100,
   "name": "accuracy",
   "random_baseline": 25,
   "unit": "%"
  },
  "name": "MMLU: Professional Accounting",
  "page_kind": "subset",
  "paper": {
   "arxiv": "2009.03300",
   "title": "Measuring Massive Multitask Language Understanding",
   "url": "https://arxiv.org/abs/2009.03300",
   "year": 2021
  },
  "publisher": {
   "authors": [
    "Dan Hendrycks",
    "Collin Burns",
    "Steven Basart",
    "Andy Zou",
    "Mantas Mazeika",
    "Dawn Song",
    "Jacob Steinhardt"
   ],
   "org": "UC Berkeley (original); Center for AI Safety (current host)",
   "url": "https://github.com/hendrycks/test"
  },
  "released": "2020-09",
  "repo_url": "https://github.com/hendrycks/test",
  "sources": [
   {
    "accessed": "2026-09-08",
    "title": "Measuring Massive Multitask Language Understanding (Hendrycks et al., arXiv:2009.03300)",
    "url": "https://arxiv.org/abs/2009.03300"
   },
   {
    "accessed": "2026-09-08",
    "title": "hendrycks/test GitHub repository (MMLU reference implementation)",
    "url": "https://github.com/hendrycks/test"
   },
   {
    "accessed": "2026-09-08",
    "title": "cais/mmlu dataset card, Hugging Face",
    "url": "https://huggingface.co/datasets/cais/mmlu"
   },
   {
    "accessed": "2026-09-08",
    "title": "cais/mmlu datasets-server size API (per-subject row counts)",
    "url": "https://datasets-server.huggingface.co/size?dataset=cais/mmlu"
   },
   {
    "accessed": "2026-09-08",
    "title": "lm-evaluation-harness mmlu_professional_accounting task config",
    "url": "https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/mmlu/default/mmlu_professional_accounting.yaml"
   }
  ],
  "status": "active",
  "subcategory": "other",
  "summary": "MMLU subject subset: Case-style problems in financial accounting, auditing, cost accounting, tax and business law.",
  "tags": [
   "knowledge",
   "multiple-choice",
   "mmlu-subset",
   "other"
  ],
  "task_format": "Four-option multiple-choice questions, graded on the single correct labelled option; commonly evaluated 5-shot, consistent with the rest of MMLU."
 }
}