Megatron-Turing NLG 530B · ANLI · Score · % ↗
2 more reported results
39.6% · Megatron-Turing NLG 530B · ANLI · Score · % · Epoch AI · ANLI ↗
36.6% · Megatron-Turing NLG 530B · ANLI · Score · % · Epoch AI · ANLI ↗
NVIDIA / MODEL EVIDENCE
5 benchmarks · 19 observations · 3 sources · released 2021-10-11
5 benchmarks · large dot: Megatron-Turing NLG 530B; small dots: closest models where reported
Megatron-Turing NLG 530B · ANLI · Score · % ↗
39.6% · Megatron-Turing NLG 530B · ANLI · Score · % · Epoch AI · ANLI ↗
36.6% · Megatron-Turing NLG 530B · ANLI · Score · % · Epoch AI · ANLI ↗
Megatron-Turing NLG 530B · HellaSwag · Overall accuracy · % ↗
82.4% · Megatron-Turing NLG 530B · HellaSwag · Overall accuracy · % · Epoch AI · HellaSwag ↗
80.24% · Megatron-Turing NLG 530B · HellaSwag · Overall accuracy · % · Epoch AI · HellaSwag ↗
80.2% · Megatron-Turing NLG 530B · HellaSwag · Overall accuracy · % · Epoch AI · HellaSwag ↗
Megatron-Turing NLG 530B · LAMBADA · Score · % ↗
76.56% · Megatron-Turing NLG 530B · LAMBADA · Score · % · Epoch AI · LAMBADA ↗
73.06% · Megatron-Turing NLG 530B · LAMBADA · Score · % · Epoch AI · LAMBADA ↗
76.6% · Megatron-Turing NLG 530B · LAMBADA · Score · % · Epoch AI · LAMBADA ↗
Megatron-Turing NLG 530B · PIQA · Score · % ↗
81.99% · Megatron-Turing NLG 530B · PIQA · Score · % · Epoch AI · PIQA ↗
80.96% · Megatron-Turing NLG 530B · PIQA · Score · % · Epoch AI · PIQA ↗
82% · Megatron-Turing NLG 530B · PIQA · Score · % · Epoch AI · PIQA ↗
Megatron-Turing NLG 530B · Winogrande · Accuracy · % ↗
73.72% · Megatron-Turing NLG 530B · Winogrande · Accuracy · % · Epoch AI · Winogrande ↗
73.01% · Megatron-Turing NLG 530B · Winogrande · Accuracy · % · Epoch AI · Winogrande ↗
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
4 of 5 shared benchmark comparisons
5 of 5 shared benchmark comparisons
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.
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
Du, Nan, Huang, Yanping, Dai, Andrew M., Tong, Simon, Lepikhin, Dmitry, Xu, Yuanzhong, Krikun, Maxim, Zhou, Yanqi, Yu, Adams Wei, Firat, Orhan, Zoph, Barret, Fedus, Liam, Bosma, Maarten, Zhou, Zongwei, Wang, Tao, Wang, Yu Emma, Webster, Kellie, Pellat, Marie, Robinson, Kevin, Meier-Hellstern, Kathleen, Duke, Toju, Dixon, Lucas, Zhang, Kun, Le, Quoc V, Wu, Yonghui, Chen, Zhifeng, Cui, Claire
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
Smith, Shaden, Patwary, Mostofa, Norick, Brandon, LeGresley, Patrick, Rajbhandari, Samyam, Casper, Jared, Liu, Zhun, Prabhumoye, Shrimai, Zerveas, George, Korthikanti, Vijay, Zhang, Elton, Child, Rewon, Aminabadi, Reza Yazdani, Bernauer, Julie, Song, Xia, Shoeybi, Mohammad, He, Yuxiong, Houston, Michael, Tiwary, Saurabh, Catanzaro, Bryan
Megatron-Turing NLG 530B