Local LLM Concurrency Challenges: Orchestration vs. Serialization
Published:Dec 26, 2025 09:42
•1 min read
•r/mlops
Analysis
The article discusses a 'stream orchestration' pattern for live assistants using local LLMs, focusing on concurrency challenges. The author proposes a system with an Executor agent for user interaction and Satellite agents for background tasks like summarization and intent recognition. The core issue is that while the orchestration approach works conceptually, the implementation faces concurrency problems, specifically with LM Studio serializing requests, hindering parallelism. This leads to performance bottlenecks and defeats the purpose of parallel processing. The article highlights the need for efficient concurrency management in local LLM applications to maintain responsiveness and avoid performance degradation.
Key Takeaways
- •The article explores a 'stream orchestration' pattern for LLM-powered assistants.
- •The architecture involves an Executor agent for user interaction and Satellite agents for background tasks.
- •Concurrency issues, particularly serialization in LM Studio, hinder the benefits of parallel processing.
Reference
“The mental model is the attached diagram: there is one Executor (the only agent that talks to the user) and multiple Satellite agents around it. Satellites do not produce user output. They only produce structured patches to a shared state.”