The provided report offers a technical deep dive into d-Matrix's Corsair architecture, an AI inference system centered on Digital In-Memory Compute (DIMC). To overcome the "memory wall" in large language model decoding, the design fuses logic directly into SRAM, achieving a claimed 150 TB/s of internal bandwidth by keeping model weights on-die. While the architecture excels at low-latency interactive tasks, the sources highlight a significant "capacity wall" because the 2 GB of SRAM per card is too small to house large models without extensive sharding across multiple cards. Performance claims like 38 TOPS/W and specific token-per-second rates remain company projections rather than independently verified benchmarks, as the firm has not yet submitted to MLPerf. Ultimately, the text positions d-Matrix as a specialized decode co-processor meant to complement GPUs rather than replace them, while noting a future roadmap toward 3D-stacked DRAM to address current memory limitations