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HellaSwag benchmark
AI model leaderboard for the HellaSwag benchmark. Compare how large language models score on HellaSwag, see the full ranking, and understand what this AI benchmark measures. Qwen2.5-7B currently leads with 89.7. Commonsense sentence-completion benchmark — pick the most plausible ending out of four for a short narrative.
Leaderboard
| # | Model | Organization | Score | Variant | Source |
|---|---|---|---|---|---|
| #1 | Qwen2.5-7B | Qwen | 89.7 | base-cited-olmo2 | official ↗ |
| #2 | Nemotron-H 56B | NVIDIA | 89 | base-10-shot | official ↗ |
| #3 | OLMo 2 32B | Allen Institute for AI | 88.5 | base-from-hf-readme | official ↗ |
| #4 | Nemotron-H 47B | NVIDIA | 87.9 | base-10-shot | official ↗ |
| #5 | Gemma 2 9B | Google DeepMind | 87.3 | base-cited-olmo2 | official ↗ |
| #6 | GPT-4o mini | OpenAI | 87.1 | cited-phi35moe | official ↗ |
| #7 | Jamba | AI21 Labs | 87.1 | cited-qwen2-57b | official ↗ |
| #8 | Mixtral 8x7B | Mistral AI | 86.5 | cited-qwen2-57b | official ↗ |
| #9 | Yi-1.5-34B | 01.AI | 85.9 | cited-qwen2-57b | official ↗ |
| #10 | Qwen2-57B-A14B | Qwen | 85.2 | base-from-hf-readme | official ↗ |
| #11 | Qwen1.5-32B | Qwen | 85 | cited-qwen2-57b | official ↗ |
| #12 | Llama 2-13B | Meta AI | 83.9 | base-cited-olmo2 | official ↗ |
| #13 | Phi-3.5-MoE | Microsoft | 83.8 | instruct-5-shot | official ↗ |
| #14 | Marin 8B | Marin | 83.6 | base-10-shot-from-hf-readme | official ↗ |
| #15 | Mistral 7B | Mistral AI | 83.31 | v0-1-cited-falcon-mamba | official ↗ |
| #16 | Nemotron-H 8B | NVIDIA | 83.23 | base-10-shot | official ↗ |
| #17 | Llama 3-8B | Meta AI | 82.23 | base-cited-falcon-mamba | official ↗ |
| #18 | Gemma 7B | Google DeepMind | 82.2 | cited-falcon-mamba | official ↗ |
| #19 | Llama 3.1-8B | Meta AI | 81.9 | base-10-shot-cited-marin | official ↗ |
| #20 | Llama 3.1-8B | Meta AI | 81.6 | base-cited-olmo2 | official ↗ |
| #21 | Gemma 2 9B | Google DeepMind | 80.9 | instruct-cited-phi35moe | official ↗ |
| #22 | Falcon Mamba | Technology Innovation Institute | 80.82 | base-from-hf-readme | official ↗ |
| #23 | Qwen2-7B | Qwen | 80.7 | base-from-hf-readme | official ↗ |
| #24 | DCLM 7B | Apple | 80.43 | from-hf-readme | official ↗ |
| #25 | Qwen2.5-7B | Qwen | 80 | cited-phi4-mini | official ↗ |
| #26 | Llama 3.2 3B | Meta AI | 77.2 | cited-phi4-mini | official ↗ |
| #27 | Mistral NeMo | Mistral AI | 76.7 | instruct-cited-phi35moe | official ↗ |
| #28 | Ministral 8B | Mistral AI | 74.6 | cited-phi4-mini | official ↗ |
| #29 | Qwen2.5-3B | Qwen | 74.6 | cited-phi4-mini | official ↗ |
| #30 | Phi-2 | Microsoft | 73.1 | cited-qwen2 | official ↗ |
| #31 | phi-3.5-mini | Microsoft | 72.2 | cited-phi4-mini | official ↗ |
| #32 | Gemma 2B | Google DeepMind | 71.4 | cited-qwen2 | official ↗ |
| #33 | Phi-4 Mini | Microsoft | 69.1 | instruct-5-shot | official ↗ |
| #34 | Gemini 1.5 Flash (Sep 2024) | Google DeepMind | 67.5 | cited-phi35moe | official ↗ |
| #35 | Qwen2-1.5B | Qwen | 66.6 | base-from-hf-readme | official ↗ |
| #36 | Qwen2-0.5B | Qwen | 49.3 | base-from-hf-readme | official ↗ |
Frequently asked questions about HellaSwag
What is the HellaSwag benchmark?
Commonsense sentence-completion benchmark — pick the most plausible ending out of four for a short narrative.
How is the HellaSwag benchmark scored?
HellaSwag is scored using the accuracy metric, where a higher score is better. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.
Which AI model scores highest on HellaSwag?
As of the latest reported scores on GenAIList, Qwen2.5-7B achieves the highest result on HellaSwag with a score of 89.7.
Is a higher HellaSwag score better?
Yes. On HellaSwag a higher score indicates better performance, so models near the top of the leaderboard are the strongest.