@perceptron
But to give you a answer which is more accurate… and maybe you can tell us your results later? We would be thankful
Manufacturing “variable costs” for a silicon chip (e.g., BrainChip’s Akida AKD2500 in a fabless model) are not a single line item — you have to separate true per-unit variable costs from volume-driven/step costs and non-recurring costs that still have to be amortized if you want real unit economics.
1) True variable manufacturing costs (scale with each unit shipped)
A) Foundry / Wafer cost
Cost_per_good_die ≈ Wafer_cost / (Gross_dies_per_wafer × Yield)
B) Assembly / Packaging (OSAT)
2) Other costs “associated with producing chips” (not clean per-unit, but volume matters)
A) NRE (non-recurring engineering) / mask costs
Not variable per chip, but you must amortize it to understand economics:
Amortized_NRE_per_unit = Total_NRE / Lifetime_units
B) EDA + IP licensing
BrainChip (fabless) typically pays:
• Foundry wafer costs
If you want to actually calculate a per-chip cost
You need (at minimum):
Hope this helps!
But to give you a answer which is more accurate… and maybe you can tell us your results later? We would be thankful
Manufacturing “variable costs” for a silicon chip (e.g., BrainChip’s Akida AKD2500 in a fabless model) are not a single line item — you have to separate true per-unit variable costs from volume-driven/step costs and non-recurring costs that still have to be amortized if you want real unit economics.
1) True variable manufacturing costs (scale with each unit shipped)
A) Foundry / Wafer cost
- Price per wafer (depends on node, wafer size, foundry, volume tiers, contract terms)
- Wafer probe / E-test (often priced per wafer or per die)
- Wafer price
- Gross dies per wafer (depends on die area + wafer geometry)
- Wafer yield (good dies / gross dies)
Cost_per_good_die ≈ Wafer_cost / (Gross_dies_per_wafer × Yield)
B) Assembly / Packaging (OSAT)
- Package type (QFN/BGA/WLCSP, etc.), pin/ball count, substrate/leadframe, thermal/reliability requirements
- Typically quoted as cost per packaged unit, but strongly volume-tiered
- ATE test time and coverage (test time is often the big driver)
- Burn-in / stress test if required
- Sampling, screening, and quality checks (some per-unit, some batch/step)
- Marking (laser), tape-and-reel, handling
- Scrap / rework / backend yield loss (assembly yield is separate from wafer yield)
- Freight between foundry → OSAT → distribution
- Duties, insurance, warehousing/handling (often ignored in “manufacturing” discussions, but it’s still per-unit/volume-linked if you’re doing landed unit cost)
2) Other costs “associated with producing chips” (not clean per-unit, but volume matters)
A) NRE (non-recurring engineering) / mask costs
Not variable per chip, but you must amortize it to understand economics:
- Mask set, tapeout, sign-off, engineering runs
Amortized_NRE_per_unit = Total_NRE / Lifetime_units
B) EDA + IP licensing
- Tooling and IP block licenses (mostly fixed/periodic)
- Sometimes running royalties depending on the deal structure
- Test program creation, characterization, reliability quals
- Reference designs, support, and variant management (grows with customers/SKUs)
- Extra test capacity, QA/reliability lots, supply-chain headcount
These don’t scale perfectly linearly; they jump at volume thresholds.
BrainChip (fabless) typically pays:
• Foundry wafer costs
- OSAT assembly + test
- Logistics/distribution
- Plus NRE/EDA/IP and ongoing engineering/support
If you want to actually calculate a per-chip cost
You need (at minimum):
- Wafer cost (with volume tier)
- Die area → gross dies/wafer
- Wafer yield (%)
- Package/assembly cost per unit
- Final test cost per unit (ATE time, multisite, coverage)
- Backend yield (%)
- Freight/duty/handling per unit (or per batch)
- Total NRE + expected lifetime units (for amortization)
Hope this helps!