unitcostai

Free tools to price AI features, compare model costs, and track pricing changes.

[unitcostai @unitcostai]

OpenAI just added GPT-5.6 Sol, Terra, and Luna.

unitcostai lets you compare their input/output costs against Claude, Gemini, Grok, Mistral, DeepSeek and Cohere, all in one place.

See what a model switch does to your margins before you ship.

https://t.co/tQRXDOgCuA

[unitcostai @unitcostai]

If it costs $9/month to run your AI feature for one customer:

- $9 is break even
- $30 gives 70% gross margin
- $45 gives 80%

Required price = cost / (1 - target margin)

https://t.co/UkRuFBM85n

[unitcostai @unitcostai]

Human review is not free.

- 10,000 AI tasks/month
- 15% need approval
- 3 minutes each
- $60/hour

That’s $4,500/month in review labor, before model or infrastructure cost.

Free calculator:
https://t.co/viFIxfc7c3

[unitcostai @unitcostai]

New tool: Human-in-the-Loop Cost Calculator.

Estimate human approval cost per AI workflow run, reviewer hours, review capacity, and when human oversight erases the savings.

Free, no login:
https://t.co/viFIxfc7c3

[unitcostai @unitcostai]

Tool calls can raise an AI agent’s cost twice: once for the browser, search, or API, and again when the output goes back into the model.

New on unitcostai: calculate the real cost per tool-using run before setting prices, credits or usage caps.

https://t.co/qPoOG7Amgb

[unitcostai @unitcostai]

New calculator: Agent Run Cost.

Estimate the cost of one completed AI agent run from model calls, prompt/tool context, retrieval, reranking, cache, infra,
and refresh work.

Useful before setting credits, caps, or per-run pricing.

https://t.co/8HyifWDgyP

[unitcostai @unitcostai]

The plan shape matters more than the model price.

Example: a $49 AI feature looks fine when typical users cost $8/mo.

If 10% of users cost $80/mo, blended cost is $15.20 and 80% margin needs a $76 price or caps/credits/top-ups.

[unitcostai @unitcostai]

A coding agent that costs $20/mo is not really $20 if the allowance disappears into retries, context rereads, or runs that produce nothing.

Start with plan price, then sanity-check it against your actual usage.

https://t.co/LEXCn43CYL

[unitcostai @unitcostai]

AI agent pricing often looks like a Stripe problem.

It usually starts one layer lower.

Stripe can handle the money event. Your app still needs to know which user, workflow, and model burned the cost.

Otherwise the plan, credit system, or usage pricing is mostly guesswork.

[unitcostai @unitcostai]

The hard part with AI pricing is not the average user.

It’s the heavy user who pays $49/mo and quietly burns $80/mo on one workflow.

That’s why I’d check cost by customer, plan, and workflow before scaling a tier.

https://t.co/2h7T2IpiCP

[unitcostai @unitcostai]

AI costs usually don't break because one call is expensive.

They break when a beta feature becomes a weekly habit for hundreds of users.

Before you change pricing, know the cost per feature and which actions are driving it.

https://t.co/EThSymXLoL

[unitcostai @unitcostai]

Don't pick a coding AI plan from model vibes alone.

Run one normal task in each tool:
- same repo
- same prompt
- time to acceptable PR

Then compare that against limits and price.

https://t.co/LEXCn43CYL

[unitcostai @unitcostai]

A model can be more token-efficient and still be the wrong default.

Use GPT-5.5 for the hard bug it solves in 1 pass.

For repo scans, code review, and routine edits, compare solved tasks before the cap hits.

https://t.co/LEXCn43CYL

[unitcostai @unitcostai]

Seat price is not the real unit for coding-agent plans.

A plan can look cheaper and still be worse if one agent session burns through the weekly cap.

Compare:
- sessions/week
- model multiplier
- overflow
- what happens when the cap hits

https://t.co/DGr1WF707w

[unitcostai @unitcostai]

GPT-5.4 vs GPT-5.5, same "internal-assistant" workload:

In this scenario GPT-5.5 adds about $0.60/user/month, so the question becomes whether it saves more than that in retries, review time, escalation, or failure cost.

https://t.co/sRxh3TxJdI

[unitcostai @unitcostai]

Standard GPT-5.5 API pricing is 2x GPT-5.4 on input and output.

That does not make it overpriced.

It also does not make it automatically worth using.

Premium models pay back when they reduce retries, review time, escalation, or failure cost enough to offset the higher token price.

Which workflows justify the premium?

https://t.co/gLDLqY5YrC

[unitcostai @unitcostai]

GPT-5.5 API pricing is live.

Standard:
- input: $5 / 1M tokens
- cached input: $0.50 / 1M tokens
- output: $30 / 1M tokens

That is 2x GPT-5.4 on input and output.

The useful question is not “is it better?” but “which workflows justify the premium?”

https://t.co/WMUpR8pTJb

[unitcostai @unitcostai]

Most “Codex vs Claude” takes skip the pricing decision. For the same workload, winner can be plan-only, plan+overflow, or usage-priced baseline.

Compare all 3 before buying credits:
https://t.co/CvDWOxCuTO

[unitcostai @unitcostai]

Most “Codex vs Claude” comparisons miss the actual pricing decision.

The cheapest option can be Codex, Claude Code, or usage-priced depending on the pricing model:

plan only, plan + overflow, or usage-priced.

https://t.co/CvDWOxCuTO

[unitcostai @unitcostai]

@boardyai Building free tools for teams to better price AI features/workflows and protect margin for their products