GPT-1 Models by OpenAI
Last refreshed 2026-04-15. Next refresh: weekly.
Details
About
The GPT-1 large language model, introduced by OpenAI in 2018, represented a major leap in natural language processing. As one of the first models to leverage the transformer architecture, GPT-1 employed a decoder-only version, enabling it to generate text that closely mimicked human language based on input prompts. Its pre-training involved a large corpus of text, notably the BooksCorpus, which equipped it with the ability to grasp intricate language patterns and relationships autonomously. However, GPT-1 was also defined by its limitations, such as a modest parameter count of 117 million and a constrained context window, which curtailed its capacity to process long-range dependencies and complex tasks as effectively as its successors. Despite these constraints, GPT-1 set the stage for the evolution of more advanced GPT models that followed, making it a foundational achievement in the field of language models 357.
Decision facts
- Best fit
- coding
- Capability starting point
- GPT-1 with 512 context
- Lowest tracked input
- Not tracked
- Closest related family
- GPT Realtime 2
Current Variants
Use-when guidance is based on each model's tracked capabilities, context window, release date, and replacement status.
Use when the workload needs 512 context and 120M parameters.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| GPT-1 | Use when the workload needs 512 context and 120M parameters. | 2018-06 | 512 context120M parameters | Current |
Release Timeline
1 release groupSpecifications(1 models)
| Model | Released | Context | Parameters |
|---|---|---|---|
| GPT-1 | 2018-06 | 512 | 120M |






