65B

65B is a shorthand commonly used in artificial intelligence to denote a class of language models that have approximately 65 billion parameters. The designation is used to group models of similar scale, lying between smaller, tens-of-billions models and the larger 70 billion and above families. In AI literature and industry discussions, 65B models are typically considered large language models designed for broad natural language understanding and generation tasks, often with capabilities in code understanding and multi-lurn dialogue.

One prominent example of a 65B model is Meta's LLaMA-65B, released in 2023 as part of the LLaMA family. Models of this size are trained on large, diverse text corpora and are usually instruction-tuned or prepared for general-purpose use through additional training steps. They are intended to balance performance with resource demands, offering strong performance on a wide range of benchmarks while remaining more demanding than smaller models.

Capabilities and limitations of 65B models vary by architecture and training regimen but typically include strong text generation, summarization, translation, and coding tasks. They can be sensitive to prompt design and may produce incorrect or biased outputs. Because of their size and training data, they also pose safety and misuse concerns, leading to restricted access or licensing for many implementations.

Hardware and deployment requirements are substantial: training generally requires large compute clusters, while inference often demands multiple high-memory GPUs or specialized optimization techniques such as quantization or offloading to achieve practical latency. As with other large language models, 65B models continue to evolve in terms of efficiency, safety, and accessibility.

See also: large language models by parameter count, LLaMA-65B.