Cerebras Brings Kimi K2.6 Inference to Enterprises

What this post added

This post details the successful deployment and performance benchmarking of the Kimi K2.6 trillion-parameter model on Cerebras hardware. It highlights achieving 981 output tokens per second, a 6.7x improvement over the next fastest GPU cloud and 23x over the median inference provider. The post explains the technical approach, including distributing weights across multiple wafers, streaming activations, and utilizing on-wafer all-to-all communication with over 200x the bandwidth of NVLink. It also mentions performing computation at 16-bit floating point while storing weights in 4-bit, combined with custom kernels and speculative decoding, to achieve this record-breaking performance for trillion-parameter MoE models.