AI Tool

Throttle Review

Throttle is an open-source command-line interface (CLI) tool designed to measure the costs and performance metrics associated with AI model deployments.

shipped Sep 25, 2026freemium

Why it matters

1Offers a freemium pricing model with a free tier available.

2Pro Early Access tier is priced at $19/month, with Standard Pricing at $50/month.

3Tracks expenses at a granular level, including $15.63 per million output tokens and $3.40 per million input tokens.

4Provides insights into performance metrics related to different AI model configurations.

About Throttle

Business Model

Open Source

Usage Pricing

$15.63 / M output tokens, $3.40 / M input tokens, $0.001344 / GPU hour per token

Funding

Bootstrapped

Platforms

CLI

Target Audience

AI developers and engineers managing model deployments

Pricing Plans

Pro Early Access

$19/mo

• Scheduled config-drift checks
• Cost history across deploys
• Alerts when a change increases cost
• Team sharing

Standard Pricing

$50/mo

• Includes all Pro features after full launch

Cost Examples

• Cost for 1 million output tokens: $15.63
• Cost for 1 million input tokens: $3.40

Leadership

Kushagra KanaujiaFounder

GitHubOpen Source

Specs

GitHub

View Repository →

API Available

Yes, public API

overview

What is Throttle?

Throttle is an AI cost management tool that enables AI developers and engineers managing model deployments to measure the costs associated with AI model deployments. It tracks expenses per million tokens while providing insights into performance metrics related to different configurations. Developed by Kushagra Kanaujia, Throttle is an open-source command-line interface (CLI) tool available on GitHub.

features

Key Features of Throttle

Throttle provides a suite of features designed to offer granular control and visibility over AI model deployment costs and performance. These capabilities are accessible via its command-line interface, allowing for integration into existing development workflows.

Measures costs per million tokens for AI model deployments.
Tracks configuration changes and their impact on cost and performance.
Includes a caching proxy for improved efficiency in AI model interactions.
Offers live endpoint cost measurement for real-time expense monitoring.
Provides insights into performance metrics related to different AI model configurations.
Tracks expenses per million tokens for both input and output.
Supports continuous monitoring of deployment cost changes.

use cases

Who Should Use Throttle?

Throttle is primarily designed for AI developers and engineers who are actively managing and optimizing AI model deployments. Its capabilities are particularly beneficial for those focused on cost efficiency and performance benchmarking.

AI developers and engineers for cost management of AI model deployments.
Teams conducting performance benchmarking for different AI model configurations.
Organizations requiring continuous monitoring of deployment cost changes for budget adherence.

how to use

How to Use Throttle

Throttle operates as a command-line interface (CLI) tool, enabling users to integrate cost and performance tracking directly into their AI development and deployment pipelines. Users can install the tool and configure it to monitor their AI model interactions.

1Install the Throttle CLI tool from its GitHub repository.
2Configure Throttle to monitor specific AI model endpoints and API calls.
3Utilize the caching proxy to optimize efficiency and reduce redundant calls.
4Run AI model deployments through Throttle to measure costs per million tokens.
5Analyze performance metrics and cost insights provided by the tool.
6Track the impact of configuration changes on overall deployment expenses.

pricing

Throttle Pricing & Plans

Throttle operates on a freemium model, offering a free tier alongside paid subscription plans for enhanced features and support. The pricing structure includes both monthly subscription fees and usage-based costs for token processing and GPU hours.

Free Tier: Includes basic cost and performance measurement capabilities.
Pro Early Access: $19/month, offering advanced features and early access to updates.
Standard Pricing: $50/month, providing full access to all features and support.
Usage Pricing: $15.63 per million output tokens, $3.40 per million input tokens, and $0.001344 per GPU hour per token.

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Pros

+Open-source component available on GitHub, fostering community contributions.
+Provides granular cost tracking per million tokens for both input and output.
+Offers performance benchmarking capabilities for different AI model configurations.
+Includes a caching proxy to enhance efficiency and potentially reduce costs.
+Features live endpoint cost measurement for real-time financial oversight.
+Supports continuous monitoring of deployment cost changes.

Cons

−Primarily a CLI tool, which may require technical proficiency for setup and use.
−Focuses on measurement rather than direct cost optimization or budget enforcement within an API gateway.
−Pricing model includes both subscription and usage-based costs, which can become complex to predict.
−Requires manual integration into existing AI deployment workflows.

Similar Tools

Throttle vs Competitors

Throttle distinguishes itself in the AI cost management landscape by focusing on measuring costs and performance for general AI model deployments via a CLI. Its competitive landscape includes tools with varying approaches to AI usage and cost tracking.

llmusage↗

It's an open-source Rust CLI that collects token usage and cost data from various AI coding tools and API providers into a single local SQLite database.

While Throttle tracks expenses per million tokens for AI model deployments, llmusage focuses on aggregating actual usage and cost data from multiple developer-centric AI tools and LLM APIs, providing a consolidated local view of your AI spending habits.

ai-cost-tracker↗

This Python library offers zero-configuration, automatic tracking of OpenAI API usage and costs with a simple import and provides CLI tools for viewing summaries.

Throttle aims to measure costs and performance for general AI model deployments, whereas ai-cost-tracker provides a highly focused, plug-and-play solution specifically for tracking actual costs of OpenAI API calls without code changes.

LiteLLM↗

LiteLLM acts as a universal proxy/gateway, providing a unified OpenAI-compatible interface to over 100 LLM providers, with built-in real-time cost tracking and budget enforcement.

Throttle is a measurement tool for existing AI deployments, while LiteLLM integrates cost tracking directly into an API gateway, allowing for real-time monitoring, budget caps, and routing across various LLM providers as part of your application's API calls.

See every Throttle alternative, compared→

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GitHubgithub.com/KushagraKanaujia/throttle