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About

LLMeter is an open source AI cost monitoring platform that gives developers one dashboard for tracking spend across OpenAI, Anthropic, DeepSeek, OpenRouter, Mistral, and Azure OpenAI. Teams connect read-only provider keys and can see real costs, daily trends, model-level breakdowns, and optimization opportunities in about 30 seconds without installing an SDK, changing endpoints, or routing production traffic through a proxy. Because requests continue going directly to the model provider, LLMeter adds no latency, does not become a point of failure, and never sees prompts or completions. Budget alerts warn teams before spending crosses daily or monthly limits, while anomaly detection identifies unexpected usage spikes before they grow. The dashboard shows which providers, models, endpoints, customers, and environments are driving costs, and OpenRouter support extends visibility across more than 500 models.

About

Pi is a minimal terminal coding harness built to adapt to developer workflows instead of forcing developers to adapt to it. It ships with powerful defaults, but stays intentionally small and aggressively extensible, letting users customize Pi with extensions, skills, prompt templates, themes, and shareable packages from npm or git. If a team needs a command, tool, provider, workflow, or UI tweak, they can ask Pi to build it, manipulate it in place, reload, and keep going. Pi supports interactive, print/JSON, RPC, and SDK modes, making it usable as a full terminal UI, a scriptable command, a JSON event stream, or an embeddable agent harness. It works with 15+ providers and hundreds of models, including Anthropic, OpenAI, Google, Azure, Bedrock, Mistral, Groq, Cerebras, xAI, Hugging Face, Kimi For Coding, MiniMax, OpenRouter, Ollama, and more, with mid-session model switching.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI developers who need to monitor multi-provider model spending and prevent unexpected cost spikes without changing their application infrastructure

Audience

Developers and AI tool builders who want a minimal, extensible terminal coding agent they can customize, script, embed, and adapt to their own workflows

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$19 per month
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Pi Agent looks really appealing from a developer’s point of view because it is simple, open-source, and focused on the actual mechanics of building coding agents. It is not trying to be a giant all-in-one platform. It gives you the core pieces: a unified LLM API, an agent loop, a terminal UI, and a coding-agent CLI. I especially like the context-engineering approach. Being able to control project instructions with AGENTS.md, customize the system prompt with SYSTEM.md, and manage long sessions through compaction makes Pi feel built for developers who actually understand how fragile agent context can be. The open-source MIT license is a big plus too. If I am building serious agent workflows, I want to inspect the harness, modify it, swap models, and understand what is happening under the hood instead of being locked into a black-box coding assistant.

Cons

  • Pi Agent is probably not the best fit for someone who wants a polished, fully managed AI coding product out of the box. It feels more like a toolkit for developers who are comfortable configuring their own workflows, choosing models, and tuning the agent behavior. I would also want to test reliability carefully before using it on production repos. Coding agents can make impressive changes, but they can also get stuck, over-edit files, miss project conventions, or make subtle mistakes if the context and guardrails are not set up well. The simplicity is a strength, but it also means you may need to bring more of your own infrastructure, evals, permissions, and safety controls.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

LLMeter
United States
www.llmeter.org

Company Information

Pi
United States
pi.dev/

Alternatives

Alternatives

Amp

Amp

Amp Code
Claude Code

Claude Code

Anthropic
Cline

Cline

Cline AI Coding Agent

Categories

Categories

Integrations

Anthropic
Claude
Microsoft Azure
Mistral AI
OpenAI
OpenRouter
Azure OpenAI Service
Cerebras
Claude Fable 5
GPT-5.5
GPT-5.5 Pro
GPT-5.6 Luna
GPT-5.6 Terra
Gemini 3.1 Pro
Graphify
Kimi K2.5
Kimi K2.6
Kimi K2.7 Code
Ollama
Slack

Integrations

Anthropic
Claude
Microsoft Azure
Mistral AI
OpenAI
OpenRouter
Azure OpenAI Service
Cerebras
Claude Fable 5
GPT-5.5
GPT-5.5 Pro
GPT-5.6 Luna
GPT-5.6 Terra
Gemini 3.1 Pro
Graphify
Kimi K2.5
Kimi K2.6
Kimi K2.7 Code
Ollama
Slack
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