metadata
license: apache-2.0
task_categories:
- text-generation
- feature-extraction
language:
- en
tags:
- gpu
- nvidia
- amd
- intel
- cuda
- hardware
- specifications
- machine-learning
size_categories:
- 1K<n<10K
GPU Database
Comprehensive GPU specifications database with architecture, manufacturing, API support, performance details, and kernel development specs.
2,824 GPUs across NVIDIA, AMD, and Intel
Part of RightNow — AI-powered code editor for GPU kernel development
Data
| Vendor | GPUs | File |
|---|---|---|
| NVIDIA | 1,286 | data/nvidia/all.json |
| AMD | 1,292 | data/amd/all.json |
| Intel | 180 | data/intel/all.json |
| All | 2,824 | data/all-gpus.json |
Schema
Each GPU contains up to 55 fields:
{
"name": "GeForce RTX 4090",
"vendor": "nvidia",
"manufacturer": "NVIDIA",
"gpuName": "AD102",
"architecture": "Ada Lovelace",
"generation": "GeForce 40",
"foundry": "TSMC",
"processSize": 5,
"transistors": 76.3,
"transistorDensity": 125.3,
"dieSize": 609.0,
"chipPackage": "BGA-2150",
"releaseDate": "2022-09-20",
"baseClock": 2235.0,
"boostClock": 2520.0,
"memoryClock": 1313.0,
"memorySize": 24.0,
"memoryType": "GDDR6X",
"memoryBus": 384,
"memoryBandwidth": 1010.0,
"shaders": 16384,
"tmus": 512,
"rops": 176,
"sms": 128,
"tensorCores": 512,
"rtCores": 128,
"coresPerSM": 128,
"l1Cache": 128.0,
"l2Cache": 72.0,
"tdp": 450,
"suggestedPSU": 850,
"powerConnectors": "1x 16-pin",
"length": 304.0,
"width": 61.0,
"slot": "Triple-slot",
"displayOutputs": "1x HDMI 2.1, 3x DisplayPort 1.4a",
"busInterface": "PCIe 4.0 x16",
"pixelRate": 443.5,
"textureRate": 1290.2,
"fp16": 82.58,
"fp32": 82.58,
"fp64": 1.29,
"directX": "12.2",
"openGL": "4.6",
"vulkan": "1.4",
"openCL": "3.0",
"cuda": "8.9",
"shaderModel": "6.8",
"warpSize": 32,
"maxThreadsPerBlock": 1024,
"maxThreadsPerSM": 1536,
"maxBlocksPerSM": 24,
"sharedMemPerSM": 102400,
"registersPerSM": 65536,
"url": "https://www.techpowerup.com/gpu-specs/geforce-rtx-4090.c3889"
}
Only populated fields are included — no nulls or zeros.
Usage
Python:
from datasets import load_dataset
ds = load_dataset("Jr23xd23/gpu-database")
Direct JSON:
import requests
gpus = requests.get(
'https://huggingface.co/datasets/Jr23xd23/gpu-database/resolve/main/data/nvidia/all.json'
).json()
rtx4090 = next(g for g in gpus if g['name'] == 'GeForce RTX 4090')
print(rtx4090['cuda']) # 8.9
print(rtx4090['maxThreadsPerSM']) # 1536
Source
Data sourced from TechPowerUp GPU Database via dbgpu.
License
Built by RightNow