LLM Serving and Tooling
Developments and releases related to serving large language models and associated developer tools.
Lo mas reciente.
The next generation of LM Studio has arrived, fundamentally decoupling its core inference engine from the desktop GUI. Version 0.4.0 introduces 'llmster,' a server-native deployment option enabling high-throughput serving via concurrent requests and continuous batching. This release signals a major shift toward enterprise and cloud deployment of local models.
Actualizaciones
2 actualizacionesLM Studio 0.4.0 Unleashes Server-Native LLM Serving with Continuous Batching and Stateful API
The next generation of LM Studio has arrived, fundamentally decoupling its core inference engine from the desktop GUI. Version 0.4.0 introduces 'llmster,' a server-native deployment option enabling high-throughput serving via concurrent requests and continuous batching. This release signals a major shift toward enterprise and cloud deployment of local models.
The Invisible Cost of AI: New Tool Brings Real-Time Token Visibility to the Terminal
As large language models become integrated into core development workflows, tracking API consumption is moving from an afterthought to a critical necessity. A new open-source utility, tokentap, offers developers a real-time, color-coded dashboard directly in the command line to monitor token usage, debug prompts, and manage context window overhead as they build.
