StratusBen

tldr: We launched https://vantage.sh/models - a price to performance comparison tool for LLMs. If you're familiar with ec2instances.info....this is basically the LLM version of that.

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I'm Co-Founder and CEO of Vantage posting on behalf of our team that shipped this. Vantage is a cloud cost management platform. We also maintain https://ec2instances.info/ after buying the site a few years back. We've been hearing rumblings from the community looking for something similar for LLMs...so we built it.

The site is free and open-source and provides a centralized view of LLM model specifications, pricing, benchmarks, and hosting information. We're shipping early and looking for feedback. Give it a peek and let us know what you think.

:wave:

Our team recently launched the ability for you to be alerted about AWS pricing changes for existing EC2 instances as well as alerts for new instances being launched and what their associated pricing is.

We've had this on in the background for a few weeks and it's alerting for new instance types faster than AWS' blog posts hit. Also whenever anything changes for existing EC2 instances you can see as soon as it changes.

If you want to set an alert, you can see this here: https://newsletters.vantage.sh/

Hi HN,

I’m on the team at www.vantage.sh and we’re releasing our remote MCP hosted on Cloudflare Workers that gives LLMs context about your structured cost and usage data on AWS, Azure, GCP, OpenAI, Datadog and ~20+ other providers. We wanted to share with this community as we know that infra cost management is already a difficult-to-understand, cumbersome task that AI can now help with.

Vantage has a set of logic for organizing costs on top of the base infrastructure level data (which we refer to as Virtual Tags) so that you can organize and allocate spend by service, business unit or function. All of that structured cost data is exposed via MCP to popular LLMs to answer specific questions about your organization.

We put together a quick explainer video on how this works here: https://www.youtube.com/watch?v=69Zt51OSjC0

Docs here: https://docs.vantage.sh/vantage_mcp

Hey all - I work at Vantage, a FinOps platform.

I know AI is peak hype right now. But it has definitely changed some of our dev workflows already. So we wanted to find a way to let our customers experiment with how they can use AI to make their cloud cost management work more productive.

The MCP Server acts as a connector between LLMs (right now only Claude, Cursor support it but ChatGPT and Google Gemini coming soon) and your cost and usage data on Vantage which supports 20+ cloud infra providers including AWS, Datadog, Mongo, etc. (You have to have a Vantage account to use it since it's using the Vantage API)

Video demo: https://www.youtube.com/watch?v=n0VP2NlUvRU

Repo: https://github.com/vantage-sh/vantage-mcp-server

It's really impressive how capable the latest-gen models are with an MCP server and an API. So far we have found it useful for:

Ad-Hoc questions: "What's our non-prod cloud spend per engineer if we have 25 engineers"

Action plans: "Find unallocated spend and look for clues how it should be tagged"

Multi-tool workflows: "Find recent cost spikes that look like they could have come from eng changes and look for GitHub PR's merged around the same time" (using it in combination with the GitHub MCP)

Thought I'd share, let me know if you have questions.