Text / LLM / Dataset

ARC-Challenge (AI2 Reasoning Challenge, Challenge Set)

Challenge Set of the ARC grade-school science multiple-choice questions: 2,590 questions answered incorrectly by both a retrieval-based and a word co-occurrence baseline; train 1,119 / dev 299 / test 1,172. (The full ARC set has 7,787 questions; the Easy Set has 5,197.)

Also known as
ARC-Challenge, ARC Challenge, ARC-C, AI2 Reasoning Challenge (Challenge Set)
Domain
science
License
CC BY-SA 4.0 (allenai/ai2_arc HF dataset card)
Homepage
allenai.org

Exposure by model

BenchmarkModelLevelReason
Classic LLM benchmarks LLM360 Amber Unknown training data not disclosed in enough detail
Classic LLM benchmarks BLOOM Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude 3.5 Sonnet Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude 3.7 Sonnet Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude 3 (Opus, Sonnet, Haiku) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Opus 4 and Claude Sonnet 4 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Fable 5 / Claude Mythos 5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Mythos Preview Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Opus 4.5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Opus 5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Claude Sonnet 5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DCLM-7B-IT (DCLM-IT-7B) Test data seen a contamination analysis found test examples in the pre-training data (32.6% of ARC-Challenge test questions are 'dirty' in DCLM-baseline (17x more than in Pile-train).) [third-party study] (via DCLM-Baseline 1.0)
Classic LLM benchmarks DCLM-7B (DCLM-Baseline-7B) Test data seen a contamination analysis found test examples in the pre-training data (32.6% of ARC-Challenge test questions are 'dirty' in DCLM-baseline (17x more than in Pile-train).) [third-party study] (via DCLM-Baseline 1.0)
Classic LLM benchmarks DeepSeek-R1-0528 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-R1-Distill Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-R1 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V3-0324 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V3.1 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V3.2-Exp Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V3.2 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V4.1-Flash Unknown training data not disclosed in enough detail
Classic LLM benchmarks DeepSeek-V4 (Pro / Flash) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemini 1.5 (Pro, Flash) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemini 2.5 (Pro, Flash) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemini 3 Pro Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemini 4 Argon Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemma 2 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemma 3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemma 3n Unknown training data not disclosed in enough detail
Classic LLM benchmarks Gemma 4 Unknown training data not disclosed in enough detail
Classic LLM benchmarks GPT-4 Test data seen a contamination analysis found test examples in the pre-training data (~3.4% of 1000 sampled ARC (Challenge set) test examples matched GPT-4 pre-training data)
Classic LLM benchmarks GPT-4o Unknown training data not disclosed in enough detail
Classic LLM benchmarks GPT-5.2 Unknown training data not disclosed in enough detail
Classic LLM benchmarks GPT-5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks GPT-6 Astra Unknown training data not disclosed in enough detail
Classic LLM benchmarks gpt-oss Unknown training data not disclosed in enough detail
Classic LLM benchmarks InternVL3.5 Unknown unknown for its base model Qwen3: training data not disclosed in enough detail
Classic LLM benchmarks InternVL3 Unknown unknown for its base model Qwen2.5: training data not disclosed in enough detail
Classic LLM benchmarks LLM360 K2-65B (K2 Diamond) Unknown training data not disclosed in enough detail
Classic LLM benchmarks K2-Horizon Unknown training data not disclosed in enough detail
Classic LLM benchmarks K2-V2 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 2 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 3.1 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 3.2-Vision (11B, 90B) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 3.2 (1B, 3B) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 3.3 70B Unknown training data not disclosed in enough detail
Classic LLM benchmarks Meta Llama 3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Llama 4 (Scout, Maverick) Unknown training data not disclosed in enough detail
Classic LLM benchmarks LLaVA-OneVision-1.5 Unknown unknown for its base model Qwen3: training data not disclosed in enough detail
Classic LLM benchmarks LLaVA-OneVision Unknown unknown for its base model SigLIP: training data not disclosed in enough detail
Classic LLM benchmarks Ministral 3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Mistral 7B Unknown training data not disclosed in enough detail
Classic LLM benchmarks Mistral Large 3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Mistral Medium 3.5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Mistral Small 4 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Mixtral 8x7B Unknown training data not disclosed in enough detail
Classic LLM benchmarks Molmo (0924) Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Classic LLM benchmarks Molmo2 Unknown unknown for its base model Qwen3: training data not disclosed in enough detail
Classic LLM benchmarks OpenAI o1 Unknown training data not disclosed in enough detail
Classic LLM benchmarks OpenAI o3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks OLMo (February 2024) Unknown training data not disclosed in enough detail
Classic LLM benchmarks OLMo 2 (November 2024) Test data seen a contamination analysis found test examples in the pre-training data (32.6% of ARC-Challenge test questions are 'dirty' in DCLM-baseline (17x more than in Pile-train).) [third-party study] (via DCLM-Baseline 1.0)
Classic LLM benchmarks Olmo 3.1 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Olmo 3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Olmo Hybrid 7B Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-3.5 (mini / MoE) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-3 (mini / small / medium) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-4-mini-flash-reasoning Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-4-mini-reasoning Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-4-mini Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-4-reasoning / Phi-4-reasoning-plus Unknown training data not disclosed in enough detail
Classic LLM benchmarks Phi-4 Not seen the authors state its test portion was excluded from training
Classic LLM benchmarks Phi-mini-MoE / Phi-tiny-MoE (SlimMoE) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Pixtral 12B Unknown training data not disclosed in enough detail
Classic LLM benchmarks Pixtral Large Unknown training data not disclosed in enough detail
Classic LLM benchmarks Pythia (deduplicated) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Pythia Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen2.5-VL Unknown unknown for its base model Qwen2.5: training data not disclosed in enough detail
Classic LLM benchmarks Qwen2.5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3-2507 (Instruct-2507 / Thinking-2507) Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3-Next Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3-VL Unknown unknown for its base model Qwen3: training data not disclosed in enough detail
Classic LLM benchmarks Qwen3.5 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3.6 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3.8-Flash-Next Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3.8 Unknown training data not disclosed in enough detail
Classic LLM benchmarks Qwen3 Unknown training data not disclosed in enough detail
Classic LLM benchmarks SmolLM2 Test data seen a contamination analysis found test examples in the pre-training data (32.6% of ARC-Challenge test questions are 'dirty' in DCLM-baseline (17x more than in Pile-train).) [third-party study] (via DCLM-Baseline 1.0)
Classic LLM benchmarks SmolLM3 Unknown training data not disclosed in enough detail

Notes

Subset of the full ARC question set (no registry id for full ARC / ARC-Easy). Questions were authored for human standardized tests; the paper says ARC includes the publicly releasable subset of the Kaggle questions. Copies found in public web data by third-party studies: Common Crawl: 336 of 1172 ARC-Challenge test examples (28.7%) flagged as present in Common Crawl (Oct 2020-Oct 2023 window); 283 (24.1%) with question and answer.

Sources