Www Nvidia Com

NVIDIA GeForce Graphics Card Specifications Skill

This skill extracts detailed GPU specification data from NVIDIA's official GeForce product specification pages at www.nvidia.com.

Overview

NVIDIA maintains comprehensive specification pages for GeForce graphics cards. This skill scrapes the structured configuration tables embedded in these pages, extracting data such as:

• GPU Engine Specs: CUDA cores, base/boost clock speeds
• Memory Specs: Memory clock, capacity, interface type, bandwidth
• Technology Support: DirectX, OpenGL, VR readiness, etc.
• Display Support: Max resolution, connectors, multi-monitor support
• Dimensions: Length, height, width
• Thermal and Power: Max temperature, power draw, system requirements

Available Functions

fetch_specs

Fetches complete specification data for a GPU.

Parameters:

• gpu_slug (required): GPU identifier from the URL, e.g., geforce-gtx-750-ti or gt-1030
• timeout (optional): Request timeout in seconds (default: 30)

Returns:

{
  "status": "success",
  "gpu_name": "GTX 750 Ti",
  "sections": [
    {
      "title": "GTX 750 Ti GPU Engine Specs:",
      "specs": [
        {"label": "CUDA Cores", "value": "640"},
        {"label": "Base Clock (MHz)", "value": "1020"},
        {"label": "Boost Clock (MHz)", "value": "1085"}
      ]
    },
    {
      "title": "GTX 750 Ti Memory Specs:",
      "specs": [
        {"label": "Memory Clock", "value": "5.4 Gbps"},
        {"label": "Standard Memory Config", "value": "2048 MB"},
        {"label": "Memory Interface", "value": "GDDR5"},
        {"label": "Memory Interface Width", "value": "128-bit"},
        {"label": "Memory Bandwidth (GB/sec)", "value": "86.4"}
      ]
    }
  ],
  "raw_specs": {
    "cuda_cores": "640",
    "base_clock_mhz": "1020",
    "boost_clock_mhz": "1085"
  },
  "url": "https://www.nvidia.com/en-us/geforce/graphics-cards/geforce-gtx-750-ti/specifications/"
}

list_key_specs

Extracts the most important GPU specifications in a simplified format.

Parameters:

• gpu_slug (required): GPU identifier
• timeout (optional): Request timeout in seconds (default: 30)

Returns:

{
  "status": "success",
  "gpu_name": "GTX 750 Ti",
  "key_specs": {
    "gpu_name": "GTX 750 Ti",
    "cuda_cores": "640",
    "base_clock_mhz": "1020",
    "boost_clock_mhz": "1085",
    "memory_config": "2048 MB",
    "memory_interface": "GDDR5",
    "memory_interface_width": "128-bit",
    "memory_bandwidth_gbps": "86.4",
    "power_w": "60 W",
    "directx": "12 API",
    "opengl": "4.4",
    "bus_support": "PCI Express 3.0",
    "length": "5.7 inches",
    "height": "4.376 inches",
    "min_system_power_w": "300 W"
  },
  "url": "..."
}

search_by_url

Fetches specification data directly from a full NVIDIA specifications page URL.

Parameters:

• url (required): Complete URL to a NVIDIA GPU specifications page
• timeout (optional): Request timeout in seconds (default: 30)

GPU Slug Examples

The gpu_slug parameter should match the URL path segment:

Dual-Variant GPUs

Some GPUs (like GT 1030) have multiple variants with different specifications. In these cases, the skill captures both values:

{
  "label": "Boost Clock (MHz)",
  "value_primary": "1379",
  "value_secondary": "1468",
  "dual_variant": true
}

Key specs for dual-variant GPUs show both values:

{
  "boost_clock_mhz": {
    "primary": "1379",
    "secondary": "1468"
  },
  "power_w": {
    "primary": "20 W",
    "secondary": "30 W"
  }
}

Example Usage

# Fetch full specifications
result = await execute({
    'function': 'fetch_specs',
    'gpu_slug': 'geforce-gtx-750-ti'
})

# Get key specs summary
result = await execute({
    'function': 'list_key_specs',
    'gpu_slug': 'gt-1030'
})

# Use direct URL
result = await execute({
    'function': 'search_by_url',
    'url': 'https://www.nvidia.com/en-us/geforce/graphics-cards/gt-1030/specifications/'
})

Notes

• The specification data is embedded directly in the HTML response (no JavaScript rendering required)
• Data is extracted from NVIDIA's proprietary coloredTable structure
• All specifications are provided as strings; numeric conversion should be done by the caller
• Some older or very new GPU models may not have specification pages available
• The skill uses aiohttp for efficient async HTTP requests