Datasetpublic

Yobitel/meta-llama-llama-3-1-70b-instructllm-quality-arithmetic-mini019e3b923a2c

meta-llama/Llama-3.1-70B-Instruct on llm.quality.arithmetic-mini (NVIDIA H100 80GB HBM3) Back to leaderboard Headline metrics Metric Value Unit N Samples 8 N Ok 8 Ok Rate 1 Accuracy 1 Accuracy P05 1 Accuracy P50 1 Accuracy P95 1 TTFT P50 32.532 ms Total P50 Ms 49.1552 Tokens Out Total 10 Run configuration Model: meta-llama/Llama-3.1-70B-Instruct @ unknown00 Engine: vllm vunknown Quantization: fp16… See the full description on the dataset page: https://huggingface.co/datasets/Yobitel/meta-llama-llama-3-1-70b-instruct__llm-quality-arithmetic-mini__019e3b923a2c.

sourceHugging Facecc-by-4.0updated 4mo agoView on Hugging Face

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meta-llama/Llama-3.1-70B-Instruct on llm.quality.arithmetic-mini (NVIDIA H100 80GB HBM3)

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Headline metrics

Metric	Value	Unit
N Samples	8
N Ok	8
Ok Rate	1
Accuracy	1
Accuracy P05	1
Accuracy P50	1
Accuracy P95	1
TTFT P50	32.532	ms
Total P50 Ms	49.1552
Tokens Out Total	10

Run configuration

—Model: meta-llama/Llama-3.1-70B-Instruct @ unknown00
—Engine: vllm vunknown
—Quantization: fp16
—Hardware: NVIDIA H100 80GB HBM3
—Driver: 580.126.09
—CUDA: 13.0
—Run date: 2026-05-18T14:51:39.436881+00:00
—Seed: 0

Verification

This result is Sigstore-signed and Rekor-logged. Verify:

bash

pip install inferencebench
bench verify hf://datasets/Yobitel/meta-llama-llama-3-1-70b-instruct__llm-quality-arithmetic-mini__019e3b923a2c/envelope.json

Rekor entry: log index -1

Methodology

See the suite methodology page.

Citation

bibtex

@misc{inferencebench_019e3b923a2c,
  title = { meta-llama/Llama-3.1-70B-Instruct on llm.quality.arithmetic-mini },
  author = { {InferenceBench community} },
  year = { 2026 },
  url = { https://huggingface.co/datasets/Yobitel/meta-llama-llama-3-1-70b-instruct__llm-quality-arithmetic-mini__019e3b923a2c },
}

Published via [InferenceBench](https://github.com/yobitelcomm/bench) — vendor-neutral AI benchmarks.