Together AI Releases Together Compiler: Agentic Continual Compilation Makes Inference Up to 2.6x Faster

Together AI has launched Together Compiler, a system that uses AI agents to perform continual compilation of inference workloads, achieving up to 2.6x speedups on model serving without changing model weights or architecture. The system works by profiling running inference jobs and iteratively recompiling execution graphs to match the observed request distribution, making it particularly effective for production workloads with variable input patterns. This is a developer-facing infrastructure tool available through the Together AI platform, targeting teams running large-scale LLM inference who want to reduce latency and cost without swapping models. The agentic compilation loop means performance improves automatically over time as the system adapts, requiring minimal manual tuning. For teams cost-sensitive about inference spend, this represents a meaningful lever beyond just model quantization or batching strategies.