Hugging Face's logo

Spaces:
delightfulrachel
/
GPUandAPIcostestimator
Sleeping

App Files Community
GPUandAPIcostestimator / README.md
delightfulrachel's picture
delightfulrachel
Update README.md
34b4396 verified
preview code
|
raw
history blame contribute delete
3.24 kB

A newer version of the Gradio SDK is available: 5.44.1

Upgrade
metadata
title: GPUandAPIcostestimator
emoji: 🌍
colorFrom: indigo
colorTo: green
sdk: gradio
sdk_version: 5.29.0
app_file: app.py
pinned: false
license: mit
short_description: A comprehensive calculator for computational usage

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Cloud GPU vs API Cost Comparison Tool

Duplicate Space

Description

A comprehensive calculator to compare the costs between self-hosted cloud hardware (AWS, GCP) and managed API endpoints (OpenAI, Anthropic, TogetherAI) for running LLMs like LLAMA, Claude, DeepSeek and GPT.

This tool helps ML engineers and developers make informed decisions about deploying large language models by:

  1. Comparing cloud GPU hardware costs vs managed API costs
  2. Calculating breakeven points for different usage patterns
  3. Considering factors like model size, compute hours, token volume
  4. Providing recommendations based on your specific workload

Features

  • Cost comparison across major cloud providers (AWS, GCP)
  • API pricing from leading LLM providers (OpenAI, Anthropic, TogetherAI)
  • Support for different model sizes (7B to 180B parameters)
  • Advanced options like reserved instances and spot pricing
  • Breakeven analysis to determine when cloud becomes cheaper than API
  • Visual comparison charts and detailed recommendations

Why Use This Tool?

For ML Teams & Engineers

  • Make data-driven decisions between building inference infrastructure or using APIs
  • Understand cost implications for different model sizes and workloads
  • Optimize existing LLM deployment costs
  • Plan budgets for AI projects more accurately

For Management & Decision Makers

  • Visualize cost comparisons between build vs buy options
  • Understand the financial impact of different deployment strategies
  • Get clear recommendations based on your specific usage patterns
  • Make informed decisions about AI infrastructure investments

How It Works

The tool considers several factors in its calculations:

  • Compute Hours: How many hours per month your model will run
  • Token Volume: How many tokens (input/output) you'll process monthly
  • Model Size: Memory requirements for different parameter counts
  • Hardware Specs: GPU types, memory, and pricing for different cloud instances
  • API Pricing: Current rates from major LLM API providers
  • Advanced Options: Discounts available through reservations or spot instances

Usage

  1. Set your usage parameters (compute hours, tokens, model size)
  2. Adjust advanced options if needed
  3. Click "Calculate Costs" to see the comparison
  4. Review the recommendation and cost analysis

About

This tool helps you make data-driven decisions about whether to build your own infrastructure or leverage managed APIs for your LLM deployments.

Perfect for teams evaluating deployment options, budgeting for ML projects, or optimizing existing infrastructure costs.

Author

Rachel Abraham at The Marmalade Group LLC | Data last updated: May 2025

SDK Version

sdk_version: 4.15.0