vLLM KV Cache Faces Cerebras Compatibility Issues

The last dimension of the vLLM KV cache tensor shape, 656, represents the byte-level size of the structure rather than the number of elements.

These 656 bytes consist of fp8 compressed MLA latent variables (512B), fp32 tile scales (16B), and bf16 RoPE components (128B), featuring a complex memory layout that depends on the warp lane write pattern of CUDA kernels.

While vLLM abstracts transport protocols such as UCX and RDMA, it does not abstract the data format itself, meaning Cerebras runtimes cannot implement the interface without replicating vLLM scheduler objects.

Although AWS (Trainium→Cerebras) and AMD (Helios→Cerebras) have launched disaggregated inference products, the lack of a standardized ABI makes cross-vendor cache transfer difficult.