Contamination MapText / LLM / Dataset
WinoGrande
44k Winograd-schema-style pronoun/option resolution problems (43,972 in WinoGrande_all: 40,938 train, 1,267 dev, 1,767 test); the debiased set has 12,282 instances (9,248 / 1,267 / 1,767). Test labels are not released (leaderboard only).
- Also known as
- WinoGrande, WinoGrande XL
- Domain
- commonsense
- License
- Dataset CC-BY; code Apache-2.0 (allenai/winogrande README)
- Homepage
- github.com
Exposure by model
| Benchmark | Model | Level | Reason |
|---|---|---|---|
| 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) | Unknown | training data not disclosed in enough detail |
| Classic LLM benchmarks | DCLM-7B (DCLM-Baseline-7B) | Unknown | training data not disclosed in enough detail |
| 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 (~0.9% of 1000 sampled WinoGrande 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 | Test data seen | a contamination analysis found test examples in the pre-training data (6% of Winogrande examples considered contaminated; estimated gain -0.1 / -0.1 / -0.2 (no benefit).) |
| 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) | Unknown | training data not disclosed in enough detail |
| 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 | Unknown | training data not disclosed in enough detail |
| Classic LLM benchmarks | SmolLM3 | Unknown | training data not disclosed in enough detail |
Notes
Copies found in public web data by third-party studies: Common Crawl: 14 of 1267 WinoGrande dev examples (1.1%) flagged as present in Common Crawl (Oct 2020-Oct 2023 window); minimal. Dev split, not test.
Sources
- WinoGrande: An Adversarial Winograd Schema Challenge at Scale (arXiv v2) · paper · retrieved 2026-10-15
- allenai/winogrande README · readme · retrieved 2026-10-15
- allenai/winogrande dataset card · dataset card · retrieved 2026-10-15