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AlpacaEval 2 benchmark
AI model leaderboard for the AlpacaEval 2 benchmark. Compare how large language models score on AlpacaEval 2, see the full ranking, and understand what this AI benchmark measures. DeepSeek-V3 currently leads with 66.5%. GPT-4-judge LLM preference benchmark — length-controlled.
Leaderboard
| # | Model | Organization | Score | Variant | Source |
|---|---|---|---|---|---|
| #1 | DeepSeek-V3 | DeepSeek | 66.5% | official ↗ | |
| #2 | GPT-4o (Nov 2024) | OpenAI | 65% | lc-win-cited-tulu3 | official ↗ |
| #3 | dots.llm1 | Rednote | 64.4% | GPT-4o judge | official ↗ |
| #4 | Granite 3.2 8B | IBM | 61.19% | instruct-from-hf-readme | official ↗ |
| #5 | EXAONE 3.5 32B | LG AI Research | 60.6% | instruct-from-hf-readme | official ↗ |
| #6 | EXAONE 3.5 7.8B | LG AI Research | 54.2% | instruct-from-hf-readme | official ↗ |
| #7 | DeepSeek-V3 | DeepSeek | 53.5% | lc-win-cited-tulu3 | official ↗ |
| #8 | Gemma 2 27B | Google DeepMind | 52.2% | instruct-cited-exaone35 | official ↗ |
| #9 | Tulu 3 405B | Allen Institute for AI | 51.4% | instruct-lc-win | official ↗ |
| #10 | DeepSeek-V2.5 | DeepSeek | 50.5% | from-hf-readme | official ↗ |
| #11 | Qwen2.5 Instruct (72B) | Qwen | 47.7% | instruct-lc-win-cited-tulu3 | official ↗ |
| #12 | Gemma 2 9B | Google DeepMind | 43.7% | instruct-lc-win-cited-tulu3 | official ↗ |
| #13 | Granite-4.0-H-Small | IBM | 42.48% | official ↗ | |
| #14 | Qwen2.5-32B | Qwen | 41% | instruct-cited-exaone35 | official ↗ |
| #15 | Llama 3.1-405B | Meta AI | 38.5% | instruct-lc-win-cited-tulu3 | official ↗ |
| #16 | EXAONE 3.5 2.4B | LG AI Research | 37.1% | instruct-from-hf-readme | official ↗ |
| #17 | Yi-1.5-34B | 01.AI | 34.8% | instruct-cited-exaone35 | official ↗ |
| #18 | Granite 3.2 2B | IBM | 34.51% | instruct-from-hf-readme | official ↗ |
| #19 | Tulu 3 8B | Allen Institute for AI | 34.5% | instruct-lc-win | official ↗ |
| #20 | Llama 3.1-70B | Meta AI | 33.4% | instruct-lc-win-cited-tulu3 | official ↗ |
| #21 | Qwen2.5-7B | Qwen | 31.7% | instruct-cited-exaone35-7b | official ↗ |
| #22 | Granite-4.0-H-Micro | IBM | 31.49% | official ↗ | |
| #23 | Ministral 8B | Mistral AI | 31.4% | instruct-lc-win-cited-tulu3 | official ↗ |
| #24 | Granite-4.0-H-Tiny | IBM | 30.61% | official ↗ | |
| #25 | Granite 3.1 8B | IBM | 30.34% | instruct-cited-granite-3-2 | official ↗ |
| #26 | Qwen2.5-7B | Qwen | 30.34% | instruct-cited-granite-3-2 | official ↗ |
| #27 | Hermes 3 405B | Nous Research | 30.2% | lc-win-cited-tulu3 | official ↗ |
| #28 | Gemma 2 2B | Google DeepMind | 29.1% | instruct-cited-exaone35 | official ↗ |
| #29 | Hermes 3 70B | Nous Research | 28.4% | lc-win-cited-tulu3 | official ↗ |
| #30 | Llama 3.1-8B | Meta AI | 27.22% | instruct-cited-granite-3-2 | official ↗ |
| #31 | Granite 3.1 2B | IBM | 27.17% | instruct-cited-granite-3-2 | official ↗ |
| #32 | Llama 3.1-8B | Meta AI | 25.7% | instruct-cited-exaone35 | official ↗ |
| #33 | Llama 3.1-8B | Meta AI | 24.2% | instruct-lc-win-cited-tulu3 | official ↗ |
| #34 | DeepSeek-R1-Distill-Llama-8B | DeepSeek | 21.85% | cited-granite-3-2 | official ↗ |
| #35 | Llama 3.2 3B | Meta AI | 18.7% | instruct-cited-exaone35 | official ↗ |
| #36 | Qwen2.5-3B | Qwen | 17.4% | instruct-cited-exaone35 | official ↗ |
| #37 | DeepSeek-R1-Distill-Qwen-7B | Qwen | 15.35% | cited-granite-3-2 | official ↗ |
| #38 | DeepSeek-R1-Distill-Qwen-7B | DeepSeek | 15.35% | cited-granite-3-2 | official ↗ |
| #39 | Qwen2.5-1.5B | Qwen | 8.4% | instruct-cited-exaone35 | official ↗ |
Frequently asked questions about AlpacaEval 2
What is the AlpacaEval 2 benchmark?
GPT-4-judge LLM preference benchmark — length-controlled.
How is the AlpacaEval 2 benchmark scored?
AlpacaEval 2 is scored using the win-rate (%) metric, where a higher score is better. The maximum achievable score is 100.000. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.
Which AI model scores highest on AlpacaEval 2?
As of the latest reported scores on GenAIList, DeepSeek-V3 achieves the highest result on AlpacaEval 2 with a score of 66.5%.
Is a higher AlpacaEval 2 score better?
Yes. On AlpacaEval 2 a higher score indicates better performance, so models near the top of the leaderboard are the strongest.