PeriFlow Reviews

Speed: It is significantly faster than other serving frameworks, making it highly efficient for serving Large Language Models (LLMs) and Large Multimodal Models (LMMs).

Cost-Effective: It offers substantial cost savings, reducing GPU costs by 40-80%.

Support for Various Models: It supports a wide range of generative AI models, including quantized models and Mixture of Experts (MoE).

Innovative Features: It offers unique features like iteration batching, a DNN library, Friendli TCache, and speculative decoding, which contribute to its high performance and efficiency.

Multiple Deployment Options: It provides various ways to run generative AI models, including Friendli Container, Friendli Dedicated Endpoints, and Friendli Serverless Endpoints.

Limited Public Availability: The Friendli Engine is not publicly available, and outside sources are not able to compare it directly with other LLM frameworks.

Patent Restrictions: Some of its optimizations, like iteration batching, are protected by patents in the US and Korea, and cannot be used without authorization.

Pricing Transparency: For some services, such as Friendli Container for production environments and enterprise plans for Friendli Dedicated Endpoints, you need to contact sales for pricing details, which may not provide immediate transparency on costs.