I bought four NVIDIA CMP 100-210 cards off the secondhand market for about $130 each. They are ex-mining cards based on the

Volta GV100 die — same silicon as the V100 — with 16 GB of HBM2 each. On paper, four of them give me 64 GB of HBM2 for

the price of a single used 3090.

In practice, NVIDIA had crippled them in hardware.

The throttle

The CMP 100-210 has its tensor cores throttled 64×. HMMA latency is stretched from 8 cycles to 512. cuBLAS WMMA caps out

at about 5 TFLOP per card. PCIe is locked to Gen1 x1, no P2P, no NVLink. CUPTI is blocked, so you can't even use NVIDIA's

own profiler.

The throttle is enforced by an e-fuse + PMU bootrom double-lock on the die. This isn't a firmware switch — it's blown into

the silicon. There is no software unlock. (Yes, I tried.)

The result: anything that goes through cuBLAS tensor cores runs at 1/64 speed or fails outright. That's vLLM, llama.cpp's

default cuBLAS path, FlashAttention, bitsandbytes, PyTorch's default matmul.…