Token Economics Calculator for AI inference hardware

Details

External ID

45980031

Source

HN

Company

—

Product

Token Economics Calculator for AI inference hardware

Website domain

tensordyne.ai

Launched

Nov. 19, 2025

Cohort

—

Upvotes

13

Upvotes percentile

0.5796943231441049

Tags

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Fetched at

Sept. 7, 2026, 9:25 p.m.

Updated at

Sept. 7, 2026, 9:25 p.m.

Description

Hi HN,I'm Paul from Tensordyne. We build AI inference systems and chips on logarithmic math. We've put together an interactive Token Economics Calculator to help make apples-to-apples comparisons of inference hardware across vendors:<https://www.tensordyne.ai/token-economics-calculator>We're interested in how closely it lines up with the community's view of the market.Why we built thisInvestors and customers kept asking how our system compares to others (NVIDIA and a growing list of startups). Plenty of publicly available data exists, but it's scattered and inconsistent. News articles, provider sites, Artificial Analysis, MLCommons, and now SemiAnalysis’s new InferenceMAX all publish useful numbers — but using different metrics. That makes “what’s actually better (and at what cost)?” surprisingly hard to answer, especially across the broad range of system providers.What the calculator does- Scenario-normalized comparisons: we’ve chosen a few model scenarios and normalized data from different sources to the same key metrics.- Capacity modeling: we estimate racks needed to support a target user load based on model size and KV-cache needs.- Cost & power economics: we estimate tokens/$ and tokens/kWh. You can input your own capex, amortization, colocation and energy costs and see how that impacts TCO.- Architecture: see how different memory architectures (e.g. SRAM-only vs. HBM) could impact profitability.- Like-for-like: see how model performance varies significantly depending on use case by comparing two configurations for the same model.Data sources & gapsWe pull from publicly available materials. Where numbers are missing, we estimate (e.g. from chip size / process / HBM capacity) to take a first cut at pricing — and let you swap in your own values.What we’re hoping to learn from you- Which metrics matter most for your use case.- Where our defaults are off (power, users, utilization, etc.).- Systems we should add (including startups) and links to data.If you try it, please tell us what’s confusing, missing, or flat-out wrong.We’ll be in the thread answering questions.

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