GitHub Spark - AI Developer Tools Tool

Overview

GitHub Spark (from GitHub Next) is an AI-first, no-code/low-code platform for creating, iterating, and sharing small web apps (“sparks”) using natural language and visual editing. Spark pairs a natural-language editor (with interactive previews, revision variants, automatic history and model selection) with a managed runtime that provides deployment-free hosting, persistent key/value storage, theming, built-in authentication, and integrated model prompting. Sparks are accessible from a PWA-enabled dashboard and can be shared as read-only or read-write, or remixed by others to create derivative versions. (Source: GitHub Next project page.) The product is positioned as a tool for rapid, personal app creation — examples range from a simple allowance tracker to a custom HackerNews reader — aimed at lowering the cost and complexity of building highly tailored micro apps. Spark supports multiple LLMs and exposes the prompts used by the runtime so creators can tune generative behaviors without editing application code. As of the public preview, GitHub is iterating the feature set with early users and plans to expand collaboration, runtime integrations, and storage capabilities over time. (Sources: GitHub Next project page; GitHub documentation.)

Key Features

• Natural-language editor with live interactive previews and immediate execution.
• Revision variants: generate 3–6 alternative revisions for rapid exploration.
• Automatic history: every revision saved and restorable with one click.
• Multi-model selection: pick among several LLMs for generation and iteration.
• Managed runtime with deployment-free hosting and PWA installation.
• Persistent managed key/value data store and visual data editor.
• Integrated prompt editor to view and tweak prompts used by a spark.
• Themed UI system and component library for polished, consistent visuals.
• Share, favorite, and remix sparks with read-only or read-write permissions.

Example Usage

Example (python):

import requests
from bs4 import BeautifulSoup

# Lightweight example: fetch the Spark landing page and print the page title.
# This does not interact with Spark programmatically (no public Spark API is documented).
SPARK_URL = "https://githubnext.com/projects/github-spark"

resp = requests.get(SPARK_URL, timeout=10)
resp.raise_for_status()

soup = BeautifulSoup(resp.text, "html.parser")
title = soup.title.string.strip() if soup.title else "(no title found)"
print(f"Fetched: {SPARK_URL}\nPage title: {title}")

Pricing

Spark is offered as part of GitHub Copilot premium tiers (Copilot Pro+ and Enterprise). Copilot Enterprise is listed at $39 USD per user per month and includes Spark access and entitlements (e.g., up to 250 Spark messages/month, 10 concurrent building sessions). Billing specifics: each Spark prompt consumes 4 premium requests; premium requests beyond your plan’s allowance are billed at $0.04 USD per request (so a single Spark prompt costs $0.16 beyond allowance). Deployed sparks currently do not incur direct charges but are subject to usage limits; GitHub plans additional billing controls in the future. (Sources: GitHub features page; GitHub Docs — Billing for Spark.)

Benchmarks

Copilot Enterprise price (includes Spark): $39 USD per user per month (Source: https://github.com/features/spark)

Premium request consumption per Spark prompt: Each Spark prompt consumes 4 premium requests (Source: https://docs.github.com/en/copilot/concepts/billing/billing-for-spark)

Marginal cost for premium requests beyond plan allowance: $0.04 USD per premium request (so $0.16 per Spark prompt beyond allowance) (Source: https://docs.github.com/en/copilot/concepts/billing/billing-for-spark)

Included Spark messages (Enterprise note): Up to 250 Spark messages included per month (Enterprise offering) (Source: https://github.com/features/spark)

Concurrent app-building sessions (Enterprise): 10 active app building sessions at a time (Enterprise) (Source: https://github.com/features/spark)

Key Information

• Category: Developer Tools
• Type: AI Developer Tools Tool