Throughput llama 8b long

workload	vanilla vLLM	nnsight eager	nnsight taps (CUDA graphs)	interp-engine vllm	interp-engine vllm-static	vLLM-Lens
generate	90	84	87	85	87	85
generate, 8 concurrent	574	539	558	537	553	539
capture 1 layer, every step	·	77	87	84	87	76
capture every layer, every step	·	66	86	48	67	38
capture 1 layer, 8 concurrent	·	530	553	528	544	468
additive steering, 1 layer	·	75	86	84	87	50
logit lens every step	·	77	82	65	64	48
linear probe every step	·	75	86	83	87	49
zero one attention head every step	·	77	87	✗	✗	✗
override the sampled token every step	·	76	87	✗	✗	✗
sweep: 1024 × 1 token, capture 1 layer, per request	0.76 s	1.64 s	1.54 s	·	·	1.35 s
sweep: 1024 × 1 token, capture 1 layer, edit() once	·	1.12 s	1.03 s	·	·	✗