r/costlyinfra

🚀 Save on LLM Costs? Help Me Build the Perfect Token Archiving Tool!
â–˛ 7 r/costlyinfra+2 crossposts

🚀 Save on LLM Costs? Help Me Build the Perfect Token Archiving Tool!

To all developers, indie hackers, and tech leads out there,

Are your OpenAI and Anthropic API bills getting out of hand? đź’¸

I am currently building a Token Savings SaaS product designed to help developers and companies optimize, cache, and archive their AI prompts and responses to drastically cut down on API expenses.

To build the best possible solution, I need to understand your actual pain points and current spending habits. Whether you are a solo hacker spending $10/month or an enterprise spending $5,000+, your input is incredibly valuable.

Could you spare 60 seconds to fill out this quick, anonymous Google Form?

👉 https://docs.google.com/forms/d/e/1FAIpQLSfyuJuzceGgZxqilY6WEsNiHFRtuW9wGGjYQ3w-Rqw3HhEi6g/viewform?usp=dialog

What's in it for you?
Leave your email at the end of the survey if you want early beta access and a permanent discount once we launch!

Thank you for your time and feedback! Let me know your thoughts or questions in the comments below.

docs.google.com
u/Effective-Tangelo-38 — 5 days ago
â–˛ 1 r/costlyinfra

We resold an AI API at a loss for three weeks because we priced per second and they billed per pixel

Cautionary tale for anyone building on top of someone else's model API and charging users for the output.

We added AI video generation to our product (socialshot.ai, product photos and video for ecommerce). The provider's docs and every pricing summary I could find described the video model in per second terms, so we did the obvious thing: worked out cost per second, added margin, charged users per second of output. On paper, roughly 70% margin.

Then I opened the provider's actual billing dashboard and read the line items for real jobs instead of trusting the docs. They bill by pixel area, not by duration. Which meant:

720p margin was really about 50%, not 70%.

1080p was negative. Every single 1080p render lost us money, and 1080p was the tier we were actively upselling.

Failed generations still bill. A request that errors and returns nothing to the user is still a charge on our side.

Three things I'd do differently, and would suggest to anyone reselling model APIs.

One: never derive unit economics from documentation, a pricing page summary or a search result. Run one real job of each type and each resolution, then read the invoice line for that specific job. Separately from this, we caught a search snippet that was wrong about a model's price by 15 to 25 times. Docs lag, blogs guess, invoices don't.

Two: price on the same unit your provider bills you on. If they bill by pixel area and you charge by second, you haven't set a margin, you've placed a bet on what resolution your users pick. Worst case is that your premium tier becomes your biggest loss maker, which is exactly what happened here, because the customers who trust you most buy the tier that costs you most.

Three: model your failure rate as a cost, not an exception. If errored calls bill, your effective cost per successful generation is higher than the quoted cost, and it degrades under load, which is precisely when your volume is highest. Also decide upfront what happens when a provider silently gives you less than you asked for. Ours can quietly return a shorter clip than requested, so we had to add verification of delivered output and a pro rated refund, otherwise the customer pays for 10 seconds and gets 6.

The fix in our case was routing the expensive path onto a cheaper variant of the same model. Funny side effect: our premium feature is now more profitable than the standard one.

Same theme on the image side: our image model bills roughly 0.18 to 0.19 dollars per call and also charges for failures. Small numbers that matter enormously when your retail price is cents per image.

Has anyone else been burned by a provider's billing unit not matching its docs? Curious whether this is a video specific mess or standard across the model APIs.

reddit.com
u/DryProgress9179 — 8 days ago
â–˛ 15 r/costlyinfra+5 crossposts

I collected 197 tools, papers and practices for reducing AI token waste

After building a multi-agent research pipeline, I realized that useful information about AI token efficiency is scattered everywhere.

There are separate tools and papers for:

- token monitoring
- prompt and semantic caching
- context compression
- model routing
- memory
- multi-agent orchestration
- pricing and benchmarks
- verification and evaluation

So we started collecting the best resources in one place.

The result is Awesome AI Tokenomics, currently with 197 verified entries across tools, research, practices, concepts, claims, and reusable setups.

It is not meant to be only another long link list. We also track maintenance and freshness, require primary sources, and keep the descriptions factual.

I would especially appreciate feedback on:

- important projects we missed
- categories that should be reorganized
- claims that need stronger evidence
- practical token-saving setups worth adding

Disclosure: I maintain this repo as part of my work at Quesma.

https://github.com/QuesmaOrg/awesome-ai-tokenomics

u/Bartaseth — 10 days ago
â–˛ 5 r/costlyinfra

Here’s how much my $200/month Claude subscription would cost at API prices

Here’s how much my $200/month Claude subscription would cost at API prices

I pay $200/month for Claude Max and use Claude Code pretty heavily. And I'm worried because Claude to discontinue their $200 plans

So I started wondering: if I made the exact same usage through the API, what would I actually be paying?

I pulled my usage and priced the tokens at Anthropic’s published API rates.

$200 subscription
$1795 equivalent API usage

That’s a pretty wild subsidy if you're a heavy user.

Obviously API price isn't Anthropic's actual compute cost, but it does make me wonder how long flat-rate pricing survives as people use agents more heavily.

Anyone else calculated their monthly Claude usage at API prices?

reddit.com
u/Frosty-Judgment-4847 — 14 days ago