Together Compiler Hits 2.6x Speedups on Frontier Model Inference
An agent loop that continuously recompiles inference engines against live traffic could shift how serving providers keep pace with rapidly changing model architectures, replacing static hand-tuned kernels. Teams running inference infrastructure or building MoE serving stacks can study the tiered persistent engine design and context-management ablations for their own optimizer setups. The results also benchmark directly against open source engines on Chinese frontier models like DeepSeek v4.1 Flash and Kimi K3, a useful comparison point when evaluating serving providers.
