datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cross-hardware-reproducibility
Cross-hardware reproducibility of LLM evaluation results (item level)
Same model, same prompts, same decode settings, different machine: does each item get the same
answer? This dataset holds the item-level evidence behind the preprint "Same model, same prompts,
different answers: item-level cross-hardware reproducibility of LLM evaluation results"
(Nicholas Templeman, CSOAI Ltd (Council of AI), 2026). The PDF is in this repository:
paper/paper.pdf; its LaTeX source, with the… See the full description on the dataset page: https://huggingface.co/datasets/csoai/cross-hardware-reproducibility.TroLL-Logic-Locking-based-Hardware-Trojanshardware_code_and_sec_smallhardware_code_and_sec_medianmodelfit-hardware-dataset
ModelFit: Local LLM Hardware Compatibility Dataset
An open dataset of which local AI models (Ollama) fit which hardware, by
parameter size, quantization, minimum RAM, and estimated memory load, across
Apple Silicon Macs, iPhones, and NVIDIA GPUs.
Maintained by ModelFit. Browse it as an interactive
table at modelfit.io/data; the canonical
machine-readable source is
modelfit.io/api/dataset.
156 models across 27 families (116 with a registry-verified local build, 40 cloud-only… See the full description on the dataset page: https://huggingface.co/datasets/modelfit/modelfit-hardware-dataset.diy-project-code-based-on-hardware-imagehardware-cvdp-problems
Hardware Design AI Training Dataset
This dataset contains processed hardware design problems and Verilog code for training AI models.
Contents
CVDP Problems: 160 evaluation problems organized by domain and complexity
Training Data: Instruction-code pairs for hardware design
Metadata: Rich annotations for each problem
Usage
from datasets import load_dataset
dataset = load_dataset("AbiralArch/hardware-cvdp-problems")
Categories
Module Generation… See the full description on the dataset page: https://huggingface.co/datasets/AbiralArch/hardware-cvdp-problems.firewall-hardware-end-of-life-dates-by-brand
Firewall and network security appliance hardware end-of-life dates by brand
Canonical, always-current version: https://referencesource.org/firewall-hardware-end-of-life-dates-by-brand/
Machine-readable: https://referencesource.org/firewall-hardware-end-of-life-dates-by-brand/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-26
Stale after: 2027-02-22 (past this date, prefer the canonical copy —
it re-verifies on a cadence this snapshot does not)
Records:… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/firewall-hardware-end-of-life-dates-by-brand.embedded-hardware-cot
⚡ PyIntel Embedded Hardware CoT (The Hardware Architect)
Zero-hallucination physical constraint reasoning grounded directly in 1,717 microcontrollers and development boards.
pyintel/embedded-hardware-cot is a specialized chain-of-thought (CoT) reasoning dataset designed to teach LLMs how to solve strict physical, electrical, and computational constraints in embedded systems without hallucinating specs or recommending circuits that would fry real silicon.
Grounded in… See the full description on the dataset page: https://huggingface.co/datasets/pyintel/embedded-hardware-cot.africa-synth-telecom-hardware-sensor-data-nigeria
Africa Synthetic Telecom Hardware Sensor Data Nigeria (TsFile)
This dataset is an Apache TsFile conversion of electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria, a synthetic Nigerian telecom tower hardware sensor dataset with temperature, power, voltage, humidity, vibration, health-status, and alert readings.
Source Dataset
Original dataset: electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria
Source files:… See the full description on the dataset page: https://huggingface.co/datasets/THULab/africa-synth-telecom-hardware-sensor-data-nigeria.r1-h4-trigger-hardware-15fpsai-inference-hardware-economics-2026
🚀 2026 AI Inference & Hardware Economics Telemetry Index
This repository hosts the official open-access empirical telemetry dataset for 2026 AI Inference, Silicon Architecture, and Hardware Economics, curated by EyesTech Systems & FinOps Intelligence.
Original Research Investigation:For the complete whitepaper, interactive latency calculators, and per-token TCO models, see the flagship publication at:👉… See the full description on the dataset page: https://huggingface.co/datasets/devidasmishra/ai-inference-hardware-economics-2026.africa-synth-telecom-hardware-sensor-data-nigeria
Africa Synth Telecom Hardware Sensor Data Nigeria | Africa (Electric Sheep Africa metadata inventory)
Size category: 100K<n<1M - Formats: parquet - Sector: energy - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria.modelfit-hardware-dataset
ModelFit Local LLM Hardware Compatibility Dataset
Which local AI models fit which hardware. Maps 107 LLMs (75 of them local-capable via Ollama, llama.cpp or LM Studio) to RAM/VRAM requirements at Q4_K_M quantization, so you can look up "will this model run on my machine" without guessing.
Source of truth: modelfit.io/data. This dataset is a mirror of the live JSON export at modelfit.io/api/dataset, refreshed from the same GitHub repo that generates it:… See the full description on the dataset page: https://huggingface.co/datasets/weckoai/modelfit-hardware-dataset.hardware-verilogeval-v2
hardware-verilogeval-v2
VerilogEval v2 - 471 Verilog evaluation problems
Dataset Overview
This dataset is part of a comprehensive collection of hardware design datasets for training and evaluating LLMs on Verilog/SystemVerilog code generation and hardware design tasks.
Files
verilog_eval_problems.json: 471 VerilogEval v2 problems
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset('AbiralArch/hardware-verilogeval-v2')… See the full description on the dataset page: https://huggingface.co/datasets/AbiralArch/hardware-verilogeval-v2.ai-hardware-roadmap-2026
ai-hardware-roadmap-2026
AI chip roadmap — H100/H200/B200/MI300X/GB200 specs, pricing, availability
Records: 15 | Updated: 2026-10-01
API: GET https://api.legion-api.com/hardware-roadmap
Bundle: gemmo.gumroad.com/l/mdevxu
Access gated — approved automatically.
quantum-hardware-device-physics
Neura Parse — Quantum Hardware Device Physics: Qubit Design, Coherence, Control & Scaling
A physics- and engineering-deep vertical on how qubits are built, controlled, and scaled across superconducting, trapped-ion, neutral-atom, and spin modalities (plus emerging erasure/biased-noise qubits). Device-physics derivations, coherence-limit analyses, control-stack engineering, and 2025-2026 scaling/interconnect work, with QuTiP/scqubits simulation context — expanding the general… See the full description on the dataset page: https://huggingface.co/datasets/Neura-parse/quantum-hardware-device-physics.ibm-150q-ising-hardware-results
IBM 150-Qubit Ising Hardware Results
Auditable results from a hardware-native, 150-active-qubit Ising/QAOA study on IBM ibm_fez, accompanied by an exact classical baseline and explicit scientific claim boundaries.
Headline evidence
Item
Verified value
Active physical qubits
150
Processor qubits
156
Successful hardware jobs
15
QPU usage
599 seconds
PUBs
547
Shots
2,087,936
QAOA depths
p=1 through p=8
Exact classical optimum
865 / 873, MIP… See the full description on the dataset page: https://huggingface.co/datasets/sankalpsthakur/ibm-150q-ising-hardware-results.hardwareadvicebotgrand-master-hardware-expert-litedefendable-pain-data-center-hardware-failure-v0.1
DC Hardware Failure Pain Receipt
"the rack down" — Mr. Defendable
A free pain-receipt dataset from the DefendableOS ecosystem. 7 rows · ready to read · all cited or graded · CC-BY-4.0.
Part of the 100-pack — 100 free pain-receipt datasets dropped from the Defendable Bakery to the open AI-trust community. Different theme per dataset. Same operator voice across all of them.
Tribunal begins before training. No proof, no honey. To the shed.
What's in here
7 pain… See the full description on the dataset page: https://huggingface.co/datasets/SwarmandBee/defendable-pain-data-center-hardware-failure-v0.1.AIPD_hardware_claim_oneai-ai-hardware-2026hardware_priceshardwarerecs.meta.stackexchange.comhardwarerecs.stackexchange.comMlops-Hardware-Carbon-Benchmarks
MLOps Hardware Benchmarks & Carbon Emissions
Dataset Description
This dataset contains 3,000 empirical, synthetic profiling records tracking large language model execution runs across diverse modern datacenter and consumer accelerators (including NVIDIA H100, A100, RTX 4090, and A10G). It captures token volumes, execution speeds, physical power utilization metrics, and overall computed carbon footprint weights.
Purpose and Impact
As deep learning… See the full description on the dataset page: https://huggingface.co/datasets/sohaibdevv/Mlops-Hardware-Carbon-Benchmarks.hardware-profiles
Hardware Profiles
Phone hardware profiles for estimating mobile LLM inference speed.
Snapdragon 865 (Samsung S20 FE) is the verified baseline.
🚀 dispatchAI
hardware_code_and_sec_large
Dataset Card for "Hardware Phi-1.5B Large Dataset"
✉ Correspondence to: Weimin Fu (weiminf@ksu.edu) or Xiaolong Guo (guoxiaolong@ksu.edu)
Citation Information
Please cite the following paper when using the OSHD Dataset.
@article{fuhardware,
title={Hardware Phi-1.5 B: A Large Language Model Encodes Hardware Domain Specific Knowledge},
author={Fu, Weimin and Li, Shijie and Zhao, Yifang and Ma, Haocheng and Dutta, Raj and Zhang, Xuan and Yang, Kaichen and Jin, Yier and… See the full description on the dataset page: https://huggingface.co/datasets/KSU-HW-SEC/hardware_code_and_sec_large.hardware-shailja-vgen
hardware-shailja-vgen
Shailja VGen Collection - 87 Verilog files
Dataset Overview
This dataset is part of a comprehensive collection of hardware design datasets for training and evaluating LLMs on Verilog/SystemVerilog code generation and hardware design tasks.
Files
vgen_files.json: 87 Verilog files from VGen framework
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset('AbiralArch/hardware-shailja-vgen')
# Access… See the full description on the dataset page: https://huggingface.co/datasets/AbiralArch/hardware-shailja-vgen.