# GPU Cloud Price & Availability Tracker (`genetheaiguy/gpu-cloud-price-tracker`) Actor

Real-time GPU rental prices (H100, H200, B200, A100, L40S, RTX 4090 & more) across Vast.ai, RunPod, Lambda and other clouds. One normalized dataset. MCP-ready for AI agents.

- **URL**: https://apify.com/genetheaiguy/gpu-cloud-price-tracker.md
- **Developed by:** [Gene Swank](https://apify.com/genetheaiguy) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.07 / gpu price record

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## GPU Cloud Price & Availability Tracker

**Compare real-time GPU rental prices across cloud providers in one run.** Get normalized, per-GPU-hour pricing for H100, H200, B200, A100, L40S, RTX 4090 and more — from Vast.ai, RunPod, and Lambda — as a clean dataset you can pipe into spreadsheets, dashboards, n8n/Make workflows, or AI agents via MCP.

### What does this actor do?

Renting GPUs means checking half a dozen provider consoles, each with different units (per GPU? per node? per month?), different tiers (secure vs community, spot vs on-demand), and constantly moving prices. This actor does the comparison shopping for you:

- ✅ Queries multiple GPU clouds in parallel
- ✅ Normalizes everything to **USD per GPU-hour** so offers are actually comparable
- ✅ Filters by GPU model, minimum VRAM, max price, and availability
- ✅ Returns results cheapest-first, with a `SUMMARY` key-value record of the cheapest offer per GPU model
- ✅ Works via web UI, API, schedules, and **MCP** — so Claude, Cursor, and other AI agents can ask "what's the cheapest H100 right now?" and get a real answer

### Who is this for?

- **ML engineers & researchers** deciding where to run the next training job or inference deployment
- **AI startups** watching burn rate — spot vs on-demand deltas across providers change weekly
- **FinOps / procurement teams** tracking GPU market rates over time (schedule daily runs, get a price history for free)
- **AI agents** doing autonomous cost optimization via MCP

### Output example

```json
{
  "provider": "Vast.ai",
  "gpuModel": "H100 SXM",
  "gpuCount": 8,
  "vramGb": 80,
  "pricePerGpuHourUsd": 1.87,
  "priceTotalHourUsd": 14.96,
  "availability": "available",
  "region": "US-East",
  "billingModel": "on-demand",
  "sourceUrl": "https://cloud.vast.ai/create/",
  "scrapedAt": "2026-07-14T15:04:05.000Z"
}
```

### Input options

| Field | Description | Default |
|---|---|---|
| `providers` | Which clouds to query | all supported |
| `gpuModels` | Filter, e.g. `["H100", "A100"]` | `[]` (all) |
| `minVramGb` | Minimum VRAM per GPU | 0 |
| `maxPricePerGpuHour` | Price ceiling in USD | 0 (none) |
| `onlyAvailable` | Skip sold-out capacity | true |
| `maxResultsPerProvider` | Cap per provider, cheapest first | 50 |

### Track prices over time

Schedule this actor daily (Apify → Schedules), and each run appends a timestamped snapshot. Within a month you have a GPU price history across providers — data that's genuinely hard to find anywhere else.

### FAQ

**How current is the data?** Every run fetches live data at execution time; nothing is cached between runs.

**Why is per-GPU-hour pricing the unit?** It's the only unit that makes an 8×H100 node on one provider comparable to a 1×H100 instance on another.

**Can I request another provider?** Yes — open an issue on the actor page. Providers with public pricing APIs get added fastest.

***

*Built by an AI-infrastructure engineer who got tired of tab-hopping between GPU consoles.*

# Actor input Schema

## `providers` (type: `array`):

Which GPU clouds to check. Leave default to query all supported providers.

## `gpuModels` (type: `array`):

Only return offers for these GPU models. Case-insensitive substring match (e.g. 'H100' matches 'H100 SXM' and 'H100 PCIe'). Leave empty for all GPUs.

## `minVramGb` (type: `integer`):

Filter out offers below this VRAM per GPU.

## `maxPricePerGpuHour` (type: `integer`):

Filter out offers above this hourly price per GPU. 0 = no limit.

## `onlyAvailable` (type: `boolean`):

Skip sold-out / unverified capacity where the provider exposes that signal.

## `maxResultsPerProvider` (type: `integer`):

Cap the number of records returned per provider (cheapest first).

## Actor input object example

```json
{
  "providers": [
    "vastai",
    "runpod",
    "lambda"
  ],
  "gpuModels": [
    "H100"
  ],
  "minVramGb": 0,
  "maxPricePerGpuHour": 0,
  "onlyAvailable": true,
  "maxResultsPerProvider": 50
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "providers": [
        "vastai",
        "runpod",
        "lambda"
    ],
    "gpuModels": [
        "H100"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("genetheaiguy/gpu-cloud-price-tracker").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "providers": [
        "vastai",
        "runpod",
        "lambda",
    ],
    "gpuModels": ["H100"],
}

# Run the Actor and wait for it to finish
run = client.actor("genetheaiguy/gpu-cloud-price-tracker").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "providers": [
    "vastai",
    "runpod",
    "lambda"
  ],
  "gpuModels": [
    "H100"
  ]
}' |
apify call genetheaiguy/gpu-cloud-price-tracker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,genetheaiguy/gpu-cloud-price-tracker"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/8K7uLFWMMefHoXjKb/builds/JPneHXr3ljeLAiG1Z/openapi.json