inference/research
verifiedmedium · 0.75updated 2026-10-17

Geerling llama.cpp Vulkan on rtx3060 (pc host): llama-2-7b Q4_K_M tg128 61.53 tok/s

61.53 tok/s (tg128)

Fields

id
benchmarks/geerling-vulkan-rtx3060-pc-llama-2-7b-q4km-tg128
Metric
decode_tok_s
Value
61.53
Unit
tok/s (tg128)
Model
llama-2-7b.Q4_K_M.gguf (3.80 GiB, 6.74 B params)
Methodology
THIRD-PARTY MEASURED (Jeff Geerling, geerlingguy/ai-benchmarks). llama.cpp build 933414c0b (7293), backend Vulkan, default llama-bench flags (ngl 99). Host: Intel Core Ultra 265K, 64GB DDR5, Ubuntu 25.10. Model file size 3.80 GiB, 6.74 B params, Q4_K_M. tg128 mean decode tok/s, per-request, batch 1, generation length 128. NOT aggregate. Whole-system wall power during the run 224.0 W (node scope, not device).
Measured by
third_party
Reproducible
yes
Mean power (W)
224
Power scope
node
Thermal state
unknown
notes
Source issue prints the llama-bench mean and the +/- spread; the stored value is the mean. The Pi-host rows are the same physical GPU on a PCIe-constrained host, so they are not a card ceiling.

Notes

Source issue prints the llama-bench mean and the +/- spread; the stored value is the mean. The Pi-host rows are the same physical GPU on a PCIe-constrained host, so they are not a card ceiling.

Cross-references