GPT-3 Medium · GSM8K · EM · % ↗
OpenAI / MODEL EVIDENCE
GPT-3
4 benchmarks · 10 observations · 7 sources · released 2020-06-22
Scores at a glance
4 benchmarks · large dot: GPT-3; small dots: closest models where reported
GPT-3 Medium · HellaSwag · Overall accuracy · % ↗
GPT-3 · RealToxicityPrompts & ToxiGen · Toxic prompts · expected maximum toxicity · original model comparison ↗
1 more reported result
0.52 / 1 · GPT-3 · RealToxicityPrompts & ToxiGen · Non-toxic prompts · expected maximum toxicity · original model comparison · RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models ↗
GPT-3 · Accuracy ↗
5 more reported results
76.7% · GPT-3 · Accuracy · Epoch AI · BoolQ · public result data ↗
77.5% · GPT-3 · Accuracy · Epoch AI · BoolQ · public result data ↗
76.4% · GPT-3 · Accuracy · Epoch AI · BoolQ · public result data ↗
60.5% · GPT-3 · Accuracy · Epoch AI · BoolQ · public result data ↗
60.5% · GPT-3 · Accuracy · Epoch AI · BoolQ · public result data ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
There are not enough shared scored settings to identify close comparisons reliably.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- Language Models are Few-Shot Learners ↗
All 31 authors
Brown, Tom B., Mann, Benjamin, Ryder, Nick, Subbiah, Melanie, Kaplan, Jared, Dhariwal, Prafulla, Neelakantan, Arvind, Shyam, Pranav, Sastry, Girish, Askell, Amanda, Agarwal, Sandhini, Herbert-Voss, Ariel, Krueger, Gretchen, Henighan, Tom, Child, Rewon, Ramesh, Aditya, Ziegler, Daniel M., Wu, Jeffrey, Winter, Clemens, Hesse, Christopher, Chen, Mark, Sigler, Eric, Litwin, Mateusz, Gray, Scott, Chess, Benjamin, Clark, Jack, Berner, Christopher, McCandlish, Sam, Radford, Alec, Sutskever, Ilya, Amodei, Dario
- Training Compute-Optimal Large Language Models ↗
All 22 authors
Hoffmann, Jordan, Borgeaud, Sebastian, Mensch, Arthur, Buchatskaya, Elena, Cai, Trevor, Rutherford, Eliza, Casas, Diego de Las, Hendricks, Lisa Anne, Welbl, Johannes, Clark, Aidan, Hennigan, Tom, Noland, Eric, Millican, Katie, Driessche, George van den, Damoc, Bogdan, Guy, Aurelia, Osindero, Simon, Simonyan, Karen, Elsen, Erich, Rae, Jack W., Vinyals, Oriol, Sifre, Laurent
- 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
- RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models — published result table ↗
- Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model ↗
All 20 authors
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
- Holistic Evaluation of Language Models (HELM) ↗
- Holistic Evaluation of Language Models (HELM) ↗
Names used in source tables
GPT-3 · GPT-3 Medium