Compare OpenELM vs. Orpheus TTS

OpenELM is a family of open-source language models created by Apple. By employing a layer-wise scaling approach, it effectively distributes parameters across the transformer model's layers, resulting in improved accuracy when compared to other open language models of a similar scale. This model is trained using datasets that are publicly accessible and is noted for achieving top-notch performance relative to its size. Furthermore, OpenELM represents a significant advancement in the pursuit of high-performing language models in the open-source community.

Canopy Labs has unveiled Orpheus, an innovative suite of advanced speech large language models (LLMs) aimed at achieving human-like speech generation capabilities. Utilizing the Llama-3 architecture, these models have been trained on an extensive dataset comprising over 100,000 hours of English speech, allowing them to generate speech that exhibits natural intonation, emotional depth, and rhythmic flow that outperforms existing high-end closed-source alternatives. Orpheus also features zero-shot voice cloning, enabling users to mimic voices without any need for prior fine-tuning, and provides easy-to-use tags for controlling emotion and intonation. The models are engineered for low latency, achieving approximately 200ms streaming latency for real-time usage, which can be further decreased to around 100ms when utilizing input streaming. Canopy Labs has made available both pre-trained and fine-tuned models with 3 billion parameters under the flexible Apache 2.0 license, with future intentions to offer smaller models with 1 billion, 400 million, and 150 million parameters to cater to devices with limited resources. This strategic move is expected to broaden accessibility and application potential across various platforms and use cases.