Backboard.io has developed a new inference engine that outperforms vLLM and SGLang in terms of throughput and latency when running the Qwen3.8-27B model on a single GPU. The engine achieved superior results across various input and output token configurations, with significant improvements in median time to first token and end-to-end latency. Backboard.io attributes its engine's performance to a proprietary 4-bit draft head for token proposal and full BF16 model verification, alongside an INT8-bound LM head and custom decode GEMM kernels. AI
IMPACT This development could lead to more efficient and faster inference for large language models, potentially reducing operational costs and improving user experience.
RANK_REASON The item details performance benchmarks and technical implementation of an inference engine, which falls under research and development in AI infrastructure. [lever_c_demoted from research: ic=1 ai=1.0]
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