# GPU Cloud & LLM API Price Feed (`knightly_sequoia/gpu-llm-price-feed`) Actor

Daily-verified GPU rental prices (H100, H200, B200, A100, L40S) across 13 clouds and LLM API token prices for popular open models. Every row links to the provider's own pricing page.

- **URL**: https://apify.com/knightly_sequoia/gpu-llm-price-feed.md
- **Developed by:** [sam ros](https://apify.com/knightly_sequoia) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## GPU Cloud & LLM API Price Feed

Daily-verified prices for renting AI GPUs and calling LLM APIs, in one clean dataset.

- **GPU cloud prices:** NVIDIA H100, H200, B200, A100 and L40S per GPU-hour across Lambda, RunPod, CoreWeave, Nebius, Modal, Crusoe, Vast.ai and more.
- **LLM API prices:** input and output price per 1M tokens for popular open models (gpt-oss, Llama, DeepSeek, Qwen and others) on Together AI, Fireworks, DeepInfra, Groq, Baseten and more.
- **Verified every day** against each provider's own pricing page. Every record includes the `source_url` it was checked against and the `date` it was checked.

### Use cases

- Feed a FinOps dashboard or spreadsheet with current GPU and token prices
- Pick the cheapest provider for a GPU or model before you launch a job
- Track price moves by scheduling this Actor daily

### Input

| Field | Description |
|---|---|
| `kind` | `both` (default), `gpu` or `api` |
| `gpus` | Filter by GPU id, e.g. `["h100","b200"]` |
| `models` | Filter by model id, e.g. `["gpt-oss-120b"]` |
| `providers` | Filter by provider id, e.g. `["lambda","runpod"]` |
| `cheapestOnly` | Return only the lowest price per GPU and per model |

### Output (one item per price)

```json
{
  "kind": "gpu",
  "date": "2026-10-13",
  "provider": "lambda",
  "provider_name": "Lambda",
  "item_id": "h100",
  "item_name": "NVIDIA H100",
  "variant": "SXM",
  "offering_type": "Cloud VM",
  "usd_per_gpu_hour": 3.99,
  "price_summary": "$3.99/GPU-hr",
  "source_url": "https://lambda.ai/pricing"
}
```

Prices are list prices shown publicly by each provider; always confirm on the provider's page before you buy. Data by [InferPrice](https://inferprice.pages.dev).

# Actor input Schema

## `kind` (type: `string`):

GPU hourly rental prices, LLM API token prices, or both.

## `gpus` (type: `array`):

Only these GPUs (e.g. h100, h200, b200, a100, l40s). Empty = all.

## `models` (type: `array`):

Only these model IDs (e.g. gpt-oss-120b). Empty = all.

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

Only these provider IDs (e.g. lambda, runpod, together). Empty = all.

## `cheapestOnly` (type: `boolean`):

Return just the lowest price for each GPU and each model.

## Actor input object example

```json
{
  "kind": "both",
  "gpus": [],
  "models": [],
  "providers": [],
  "cheapestOnly": false
}
```

# Actor output Schema

## `prices` (type: `string`):

Every returned price record (GPU and LLM API) as a table.

## `gpuPrices` (type: `string`):

Hourly GPU rental prices view.

## `apiPrices` (type: `string`):

Per-1M-token LLM API prices view.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("knightly_sequoia/gpu-llm-price-feed").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("knightly_sequoia/gpu-llm-price-feed").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 '{}' |
apify call knightly_sequoia/gpu-llm-price-feed --silent --output-dataset

```

## MCP server setup

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

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/QQC8OB2b7KqfONcd9/builds/805cNCqs66V2Ztf5U/openapi.json