Two 24 GB cards are not a 48 GB card. This calculator refuses to treat deviceCount = 2 plus “single device” as a merged pool.
If you run independent replicas, each replica still needs a full copy of the weights. Total VRAM across cards is not the budget for one copy. If you need tensor or pipeline parallel, this version does not invent a per-GPU split. It reports that a sharding plan is required, following the spirit of vLLM’s parallelism docs.
Unified memory is a shared CPU/GPU pool. NVIDIA DGX Spark is documented as 128 GB LPDDR5x coherent unified system memory, not 128 GB of dedicated VRAM. This catalog uses 128 GiB with a 16 GiB default reserve for OS and other processes. Host RAM is not added on top. Two Spark units are not one transparent 256 GB device.
Mixtral-8x7B-Instruct-v0.1 BF16 safetensors total_size is 93,405,585,408 bytes (~87.0 GiB) even though about 12.9B parameters are active per token. The default estimate keeps all experts resident. That is why a 24 GB card is insufficient for Mixtral BF16 regardless of “active parameter” marketing.
Calculator 0.1.0, dataset 2026-09-19.1. No tokens/s figures are derived for Spark or multi-GPU here.