inference/research
verifiedmedium · 0.75updated 2026-10-15

Argonne A100-SXM-40GB x4 llama.cpp meta-llama/Meta-Llama-3-8B b1

76.46 tok/s aggregate (batch*(in+out)/latency)

Fields

id
benchmarks/argonne-a100sxm40-llama-cpp-llama3-8b-fp16-4x-b1-128io-tps
Metric
tps_aggregate
Value
76.46
Unit
tok/s aggregate (batch*(in+out)/latency)
Model
meta-llama/Meta-Llama-3-8B
Methodology
THIRD-PARTY MEASURED (Argonne LLM-Inference-Bench, arXiv:2411.00136, All_results.csv). llama.cpp on NVIDIA A100 SXM 40GB x4, FP16/BF16, 128 in / 128 out, batch 1. Throughput = batch*(in+out)/latency = AGGREGATE across batch. Latency 3.35s.
Measured by
third_party
Reproducible
yes
Thermal state
unknown
notes
Argonne hardware matrix: A100 SXM 40GB x4/node. Framework=llama.cpp.

Notes

Argonne hardware matrix: A100 SXM 40GB x4/node. Framework=llama.cpp.

Cross-references