Llama 2-70B · GPQA diamond · Best score (across scorers) · % ↗
Meta / MODEL EVIDENCE
Llama 2-70B
25 benchmarks · 85 observations · 26 sources · released 2023-07-18
Scores at a glance
25 benchmarks · large dot: Llama 2-70B; small dots: closest models where reported
Llama 2-70B · MATH level 5 · Best score (across scorers) · % ↗
Llama 2-70B · OTIS Mock AIME 2024-2025 · Best score (across scorers) · % ↗
Llama 2-70B · ARC AI2 · Challenge score · % ↗
3 more reported results
78.3% · Llama 2-70B · ARC AI2 · Challenge score · % · Epoch AI · ARC AI2 ↗
57.4% · Llama 2-70B · ARC AI2 · Challenge score · % · Epoch AI · ARC AI2 ↗
56.5% · Llama 2-70B · ARC AI2 · Challenge score · % · Epoch AI · ARC AI2 ↗
Llama 2-70B · BBH · Average · % ↗
3 more reported results
58.5% · Llama 2-70B · BBH · Average · % · Epoch AI · BBH ↗
42.4% · Llama 2-70B · BBH · Average · % · Epoch AI · BBH ↗
51.2% · Llama 2-70B · BBH · Average · % · Epoch AI · BBH ↗
Llama 2-70B · GSM8K · EM · % ↗
7 more reported results
13.3% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
58.7% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
56.8% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
47.1% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
56.8% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
69.6% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
63.3% · Llama 2-70B · GSM8K · EM · % · Epoch AI · GSM8K ↗
Llama 2-70B · HellaSwag · Overall accuracy · % ↗
Llama 2-70B · LAMBADA · Score · % ↗
Llama 2-70B · MMLU · EM · % ↗
5 more reported results
59.9% · Llama 2-70B · MMLU · EM · % · Epoch AI · MMLU ↗
59.4% · Llama 2-70B · MMLU · EM · % · Epoch AI · MMLU ↗
69.8% · Llama 2-70B · MMLU · EM · % · Epoch AI · MMLU ↗
68.9% · Llama 2-70B · MMLU · EM · % · Epoch AI · MMLU ↗
69.9% · Llama 2-70B · MMLU · EM · % · Epoch AI · MMLU ↗
Llama 2-70B · OpenBookQA · Accuracy · % ↗
Llama 2-70B · PIQA · Score · % ↗
3 more reported results
82.8% · Llama 2-70B · PIQA · Score · % · Epoch AI · PIQA ↗
82.6% · Llama 2-70B · PIQA · Score · % · Epoch AI · PIQA ↗
82.8% · Llama 2-70B · PIQA · Score · % · Epoch AI · PIQA ↗
Llama 2-70B · TriviaQA · EM · % ↗
4 more reported results
87.6% · Llama 2-70B · TriviaQA · EM · % · Epoch AI · TriviaQA ↗
87.5% · Llama 2-70B · TriviaQA · EM · % · Epoch AI · TriviaQA ↗
85% · Llama 2-70B · TriviaQA · EM · % · Epoch AI · TriviaQA ↗
82.4% · Llama 2-70B · TriviaQA · EM · % · Epoch AI · TriviaQA ↗
Llama 2-70B · Winogrande · Accuracy · % ↗
Llama 2-70B · DTBench · Accuracy · % ↗
Llama 2-70B · CSQA2 · Score · % ↗
Llama 2-70B · General ECI · 26 October 2026 fit ↗
Llama 2 (70B) · LegalBench · Accuracy ↗
LLaMA-2-70B‡ · GSM-Plus / GSM-Symbolic · GSM-Plus accuracy · Original robustness evaluation ↗
LLaMA-2-70B · VisualWebArena · Overall task success · original agents ↗
1 more reported result
0.66% · LLaMA-2-70B · VisualWebArena · Overall task success · original agents · VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks ↗
LLaMA2-70B* · CMMLU · Five-shot subject-macro accuracy · original five-shot comparison ↗
Llama 2 / 70B · BizBench · Published task average · zero-shot and few-shot evaluation ↗
LLaMA-2-70B · SciBench · Textbook overall accuracy · prompting and tool conditions ↗
3 more reported results
1.89% · LLaMA-2-70B · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗
8.4% · LLaMA-2-70B · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗
5.14% · LLaMA-2-70B · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗
Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Incomplete · compliance rate · reported model comparison ↗
11 more reported results
40.8% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Unsupported · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
2.1% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Indeterminate · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
10.1% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Safety · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
24.4% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Humanizing · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
72.3% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · No system prompt · Contrast set · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
16.4% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Incomplete · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
19.1% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Unsupported · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
1.4% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Indeterminate · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
2.8% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Safety · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
3.7% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Humanizing · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
77.6% · Llama-2-70b · CoCoNot (Contextual Non-Compliance) · With system prompt · Contrast set · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗
LLaMA-2-70B · ClinicBench · MedQA · Accuracy · zero-shot main comparison ↗
16 more reported results
42.7% · LLaMA-2-70B · ClinicBench · MedMCQA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
54% · LLaMA-2-70B · ClinicBench · MMLU · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
67.4% · LLaMA-2-70B · ClinicBench · PubMedQA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
78.9% · LLaMA-2-70B · ClinicBench · Referral QA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
5.5 F1 points · LLaMA-2-70B · ClinicBench · Treat Recom. · F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
13.9 ROUGE-L points · LLaMA-2-70B · ClinicBench · MIMIC · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
8 ROUGE-L points · LLaMA-2-70B · ClinicBench · IU-Xray · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
8.3 ROUGE-L points · LLaMA-2-70B · ClinicBench · Hospitaliz. Summari. · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
6.8 ROUGE-L points · LLaMA-2-70B · ClinicBench · Patient Education · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
47.8 F1 entity-level points · LLaMA-2-70B · ClinicBench · BC5 · F1 entity-level · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
41.5 F1 entity-level points · LLaMA-2-70B · ClinicBench · NCBI · F1 entity-level · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
45.6 Micro F1 points · LLaMA-2-70B · ClinicBench · DDI · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
44.7 Micro F1 points · LLaMA-2-70B · ClinicBench · GAD · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
63.2 Micro F1 points · LLaMA-2-70B · ClinicBench · HoC · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
49.3% · LLaMA-2-70B · ClinicBench · Pharma. QA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
51.5% · LLaMA-2-70B · ClinicBench · Drug Inter. · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗
LLAMA 2 70B · Accuracy ↗
3 more reported results
87.7% · Llama 2-70B · Accuracy · Epoch AI · BoolQ · public result data ↗
88.6% · Llama 2 (70B) · Accuracy · Epoch AI · BoolQ · public result data ↗
85% · LLaMA-2 70B · Accuracy · Epoch AI · BoolQ · public result data ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
3 of 4 shared benchmark comparisons
3 of 4 shared benchmark comparisons
3 of 4 shared benchmark comparisons
How similarity is measured
Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- Llama 2: Open Foundation and Fine-Tuned Chat Models ↗
All 68 authors
Touvron, Hugo, Martin, Louis, Stone, Kevin, Albert, Peter, Almahairi, Amjad, Babaei, Yasmine, Bashlykov, Nikolay, Batra, Soumya, Bhargava, Prajjwal, Bhosale, Shruti, Bikel, Dan, Blecher, Lukas, Ferrer, Cristian Canton, Chen, Moya, Cucurull, Guillem, Esiobu, David, Fernandes, Jude, Fu, Jeremy, Fu, Wenyin, Fuller, Brian, Gao, Cynthia, Goswami, Vedanuj, Goyal, Naman, Hartshorn, Anthony, Hosseini, Saghar, Hou, Rui, Inan, Hakan, Kardas, Marcin, Kerkez, Viktor, Khabsa, Madian, Kloumann, Isabel, Korenev, Artem, Koura, Punit Singh, Lachaux, Marie-Anne, Lavril, Thibaut, Lee, Jenya, Liskovich, Diana, Lu, Yinghai, Mao, Yuning, Martinet, Xavier, Mihaylov, Todor, Mishra, Pushkar, Molybog, Igor, Nie, Yixin, Poulton, Andrew, Reizenstein, Jeremy, Rungta, Rashi, Saladi, Kalyan, Schelten, Alan, Silva, Ruan, Smith, Eric Michael, Subramanian, Ranjan, Tan, Xiaoqing Ellen, Tang, Binh, Taylor, Ross, Williams, Adina, Kuan, Jian Xiang, Xu, Puxin, Yan, Zheng, Zarov, Iliyan, Zhang, Yuchen, Fan, Angela, Kambadur, Melanie, Narang, Sharan, Rodriguez, Aurelien, Stojnic, Robert, Edunov, Sergey, Scialom, Thomas
- Qwen Technical Report ↗
All 48 authors
Bai, Jinze, Bai, Shuai, Chu, Yunfei, Cui, Zeyu, Dang, Kai, Deng, Xiaodong, Fan, Yang, Ge, Wenbin, Han, Yu, Huang, Fei, Hui, Binyuan, Ji, Luo, Li, Mei, Lin, Junyang, Lin, Runji, Liu, Dayiheng, Liu, Gao, Lu, Chengqiang, Lu, Keming, Ma, Jianxin, Men, Rui, Ren, Xingzhang, Ren, Xuancheng, Tan, Chuanqi, Tan, Sinan, Tu, Jianhong, Wang, Peng, Wang, Shijie, Wang, Wei, Wu, Shengguang, Xu, Benfeng, Xu, Jin, Yang, An, Yang, Hao, Yang, Jian, Yang, Shusheng, Yao, Yang, Yu, Bowen, Yuan, Hongyi, Yuan, Zheng, Zhang, Jianwei, Zhang, Xingxuan, Zhang, Yichang, Zhang, Zhenru, Zhou, Chang, Zhou, Jingren, Zhou, Xiaohuan, Zhu, Tianhang
- The Falcon Series of Open Language Models ↗
All 14 authors
Almazrouei, Ebtesam, Alobeidli, Hamza, Alshamsi, Abdulaziz, Cappelli, Alessandro, Cojocaru, Ruxandra, Debbah, Mérouane, Goffinet, Étienne, Hesslow, Daniel, Launay, Julien, Malartic, Quentin, Mazzotta, Daniele, Noune, Badreddine, Pannier, Baptiste, Penedo, Guilherme
- Mixtral of Experts ↗
All 26 authors
Jiang, Albert Q., Sablayrolles, Alexandre, Roux, Antoine, Mensch, Arthur, Savary, Blanche, Bamford, Chris, Chaplot, Devendra Singh, Casas, Diego de las, Hanna, Emma Bou, Bressand, Florian, Lengyel, Gianna, Bour, Guillaume, Lample, Guillaume, Lavaud, Lélio Renard, Saulnier, Lucile, Lachaux, Marie-Anne, Stock, Pierre, Subramanian, Sandeep, Yang, Sophia, Antoniak, Szymon, Scao, Teven Le, Gervet, Théophile, Lavril, Thibaut, Wang, Thomas, Lacroix, Timothée, Sayed, William El
- Yi: Open Foundation Models by 01.AI ↗
All 33 authors
AI, 01., :, Young, Alex, Chen, Bei, Li, Chao, Huang, Chengen, Zhang, Ge, Zhang, Guanwei, Wang, Guoyin, Li, Heng, Zhu, Jiangcheng, Chen, Jianqun, Chang, Jing, Yu, Kaidong, Liu, Peng, Liu, Qiang, Yue, Shawn, Yang, Senbin, Yang, Shiming, Xie, Wen, Huang, Wenhao, Hu, Xiaohui, Ren, Xiaoyi, Niu, Xinyao, Nie, Pengcheng, Li, Yanpeng, Xu, Yuchi, Liu, Yudong, Wang, Yue, Cai, Yuxuan, Gu, Zhenyu, Liu, Zhiyuan, Dai, Zonghong
- CMMLU: Measuring massive multitask language understanding in Chinese — published result table ↗
All 8 authors
Li, Haonan, Zhang, Yixuan, Koto, Fajri, Yang, Yifei, Zhao, Hai, Gong, Yeyun, Duan, Nan, Baldwin, Timothy
- SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models — published result table ↗
All 10 authors
Wang, Xiaoxuan, Hu, Ziniu, Lu, Pan, Zhu, Yanqiao, Zhang, Jieyu, Subramaniam, Satyen, Loomba, Arjun R., Zhang, Shichang, Sun, Yizhou, Wang, Wei
- BizBench: A Quantitative Reasoning Benchmark for Business and Finance — published result table ↗
- VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks — published result table ↗
All 10 authors
Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, Daniel Fried
- GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers — published result table ↗
- Large Language Models in the Clinic: A Comprehensive Benchmark — published result table ↗
All 19 authors
Liu, Fenglin, Li, Zheng, Zhou, Hongjian, Yin, Qingyu, Yang, Jingfeng, Tang, Xianfeng, Luo, Chen, Zeng, Ming, Jiang, Haoming, Gao, Yifan, Nigam, Priyanka, Nag, Sreyashi, Yin, Bing, Hua, Yining, Zhou, Xuan, Rohanian, Omid, Thakur, Anshul, Clifton, Lei, Clifton, David A.
- The Art of Saying No: Contextual Noncompliance in Language Models — published result table ↗
All 14 authors
Brahman, Faeze, Kumar, Sachin, Balachandran, Vidhisha, Dasigi, Pradeep, Pyatkin, Valentina, Ravichander, Abhilasha, Wiegreffe, Sarah, Dziri, Nouha, Chandu, Khyathi, Hessel, Jack, Tsvetkov, Yulia, Smith, Noah A., Choi, Yejin, Hajishirzi, Hannaneh
- Llama 2: Open Foundation and Fine-Tuned Chat Models ↗
All 68 authors
Touvron, Hugo, Martin, Louis, Stone, Kevin, Albert, Peter, Almahairi, Amjad, Babaei, Yasmine, Bashlykov, Nikolay, Batra, Soumya, Bhargava, Prajjwal, Bhosale, Shruti, Bikel, Dan, Blecher, Lukas, Ferrer, Cristian Canton, Chen, Moya, Cucurull, Guillem, Esiobu, David, Fernandes, Jude, Fu, Jeremy, Fu, Wenyin, Fuller, Brian, Gao, Cynthia, Goswami, Vedanuj, Goyal, Naman, Hartshorn, Anthony, Hosseini, Saghar, Hou, Rui, Inan, Hakan, Kardas, Marcin, Kerkez, Viktor, Khabsa, Madian, Kloumann, Isabel, Korenev, Artem, Koura, Punit Singh, Lachaux, Marie-Anne, Lavril, Thibaut, Lee, Jenya, Liskovich, Diana, Lu, Yinghai, Mao, Yuning, Martinet, Xavier, Mihaylov, Todor, Mishra, Pushkar, Molybog, Igor, Nie, Yixin, Poulton, Andrew, Reizenstein, Jeremy, Rungta, Rashi, Saladi, Kalyan, Schelten, Alan, Silva, Ruan, Smith, Eric Michael, Subramanian, Ranjan, Tan, Xiaoqing Ellen, Tang, Binh, Taylor, Ross, Williams, Adina, Kuan, Jian Xiang, Xu, Puxin, Yan, Zheng, Zarov, Iliyan, Zhang, Yuchen, Fan, Angela, Kambadur, Melanie, Narang, Sharan, Rodriguez, Aurelien, Stojnic, Robert, Edunov, Sergey, Scialom, Thomas
- Llama 2: Open Foundation and Fine-Tuned Chat Models ↗
All 68 authors
Touvron, Hugo, Martin, Louis, Stone, Kevin, Albert, Peter, Almahairi, Amjad, Babaei, Yasmine, Bashlykov, Nikolay, Batra, Soumya, Bhargava, Prajjwal, Bhosale, Shruti, Bikel, Dan, Blecher, Lukas, Ferrer, Cristian Canton, Chen, Moya, Cucurull, Guillem, Esiobu, David, Fernandes, Jude, Fu, Jeremy, Fu, Wenyin, Fuller, Brian, Gao, Cynthia, Goswami, Vedanuj, Goyal, Naman, Hartshorn, Anthony, Hosseini, Saghar, Hou, Rui, Inan, Hakan, Kardas, Marcin, Kerkez, Viktor, Khabsa, Madian, Kloumann, Isabel, Korenev, Artem, Koura, Punit Singh, Lachaux, Marie-Anne, Lavril, Thibaut, Lee, Jenya, Liskovich, Diana, Lu, Yinghai, Mao, Yuning, Martinet, Xavier, Mihaylov, Todor, Mishra, Pushkar, Molybog, Igor, Nie, Yixin, Poulton, Andrew, Reizenstein, Jeremy, Rungta, Rashi, Saladi, Kalyan, Schelten, Alan, Silva, Ruan, Smith, Eric Michael, Subramanian, Ranjan, Tan, Xiaoqing Ellen, Tang, Binh, Taylor, Ross, Williams, Adina, Kuan, Jian Xiang, Xu, Puxin, Yan, Zheng, Zarov, Iliyan, Zhang, Yuchen, Fan, Angela, Kambadur, Melanie, Narang, Sharan, Rodriguez, Aurelien, Stojnic, Robert, Edunov, Sergey, Scialom, Thomas
- Large Language Models Are Also Good Prototypical Commonsense Reasoners ↗
- Qwen Technical Report ↗
All 48 authors
Bai, Jinze, Bai, Shuai, Chu, Yunfei, Cui, Zeyu, Dang, Kai, Deng, Xiaodong, Fan, Yang, Ge, Wenbin, Han, Yu, Huang, Fei, Hui, Binyuan, Ji, Luo, Li, Mei, Lin, Junyang, Lin, Runji, Liu, Dayiheng, Liu, Gao, Lu, Chengqiang, Lu, Keming, Ma, Jianxin, Men, Rui, Ren, Xingzhang, Ren, Xuancheng, Tan, Chuanqi, Tan, Sinan, Tu, Jianhong, Wang, Peng, Wang, Shijie, Wang, Wei, Wu, Shengguang, Xu, Benfeng, Xu, Jin, Yang, An, Yang, Hao, Yang, Jian, Yang, Shusheng, Yao, Yang, Yu, Bowen, Yuan, Hongyi, Yuan, Zheng, Zhang, Jianwei, Zhang, Xingxuan, Zhang, Yichang, Zhang, Zhenru, Zhou, Chang, Zhou, Jingren, Zhou, Xiaohuan, Zhu, Tianhang
- Mixtral of Experts ↗
All 26 authors
Jiang, Albert Q., Sablayrolles, Alexandre, Roux, Antoine, Mensch, Arthur, Savary, Blanche, Bamford, Chris, Chaplot, Devendra Singh, Casas, Diego de las, Hanna, Emma Bou, Bressand, Florian, Lengyel, Gianna, Bour, Guillaume, Lample, Guillaume, Lavaud, Lélio Renard, Saulnier, Lucile, Lachaux, Marie-Anne, Stock, Pierre, Subramanian, Sandeep, Yang, Sophia, Antoniak, Szymon, Scao, Teven Le, Gervet, Théophile, Lavril, Thibaut, Wang, Thomas, Lacroix, Timothée, Sayed, William El
- DTBench — Conceptual Reasoning Index ↗
- Holistic Evaluation of Language Models (HELM) ↗
- Holistic Evaluation of Language Models (HELM) ↗
- Holistic Evaluation of Language Models (HELM) ↗
- GPQA Diamond ↗
- MATH Level 5 ↗
- OTIS Mock AIME 2024-2025 ↗
- AI benchmarks & capabilities ↗
- LegalBench — evaluation methodology and results ↗
Names used in source tables
LLAMA 2 70B · LLaMA-2 70B · LLaMA-2-70B · LLaMA-2-70B‡ · LLaMA2-70B* · Llama 2 (70B) · Llama 2 / 70B · Llama 2-70B · Llama-2-70b