Scaling Laws for Neural Language Models
by OpenAI · free · Last verified 2026-03-17
Empirically establishes power-law scaling relationships between language model performance and model size, dataset size, and compute budget. Provides the foundational framework for predicting LLM capabilities as a function of scale, guiding research for years.
https://arxiv.org/abs/2001.08361 ↗B+
B+—Good
Adoption: AQuality: A+Freshness: CCitations: A+Engagement: F
Specifications
- License
- Open Access
- Pricing
- free
- Capabilities
- scaling-analysis, empirical-prediction, compute-budgeting
- Integrations
- Use Cases
- training-budget-allocation, model-size-selection, research-planning
- API Available
- No
- Tags
- scaling-laws, compute-optimal, language-models, openai, empirical, power-law
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
76.7Adoption
88
Quality
95
Freshness
45
Citations
90
Engagement
0
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