modelrigs

Ternary Bonsai 2 27B on RTX 3090 workstation (Ryzen 9 7950X, 64 GB)

27.36B on 24 GB at 936 GB/s. Hardware details · Model details

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Yes. Ternary Bonsai 2 27B fits on RTX 3090 workstation (Ryzen 9 7950X, 64 GB) at the recommended PTQ1_0 configuration, requiring approximately 7.2 GB at 8K context. Practical context capacity is 192K.
CompatibilityComfortable
Calculated fit
Yes
Calculated Uses under 80% of usable memory. Room for a long context and other work.
Recommended quantization
PTQ1_0
Calculated gguf
Memory required
7.2 GB
Calculated of 22.1 GB usable — 33%
Max practical context
192K
Calculated model supports 256K

Memory budget at 8K context

Model weights ⓘ
5.5 GB Measured
KV cache ⓘ
0.5 GB Calculated
Runtime overhead ⓘ
1.2 GB Estimated
Total required
7.2 GB Calculated
Headroom ⓘ
14.9 GB Calculated
Smallest published ternary pack that leaves headroom: uses 33% of usable memory at 8K context.
Discrete GPU: 24 GB of VRAM, of which we assume 92% is usable after driver and context overhead.
Hybrid attention: token-growing KV memory is charged to 16 full-attention blocks. The linear-attention blocks also hold fixed-size state, so the memory estimate is approximate.
Performance

Estimated performance · recommended PTQ1_0

Decode, prefill and TTFT below are estimates for PTQ1_0. We do not have a comparable PTQ1_0 measurement on this machine.

Estimated decode
—
Estimated PTQ1_0; calculated range
Estimated prefill
—
Estimated PTQ1_0; calculated range
Estimated TTFT at 8K
~7.4–15.3 s
Estimated PTQ1_0; calculated range
Hardware load reference
600 W
Official spec hardware TDP; not this model run
No throughput figures for this configuration. We do not estimate performance for a model that cannot load.
How the estimate is calculated
  1. Decode: reading 27.4B active parameters at 1.75 bits/weight takes 8.53 ms at 936 GB/s x 75% achieved efficiency.
  2. Prefill: 142 TFLOPS (FP16) x 32% assumed model-FLOPs utilisation, divided by 2 x 27.4B parameters per token.
  • Prefill throughput is highly engine-dependent. Flash attention, batch size and quantized KV all move this number substantially, and for sparse mixture-of-experts models it is the least reliable figure we produce.
  • This is a calculated estimate, not a measurement. It assumes a single request, a short prompt, no speculative decoding and a warm model already resident in memory.

Estimator version estimator_v1. Stored with every estimated row so old estimates can be regenerated when the model improves.

Submit a benchmarkSubmissions stay pending until reviewed.
This model at other quantizations on this machine
QuantizationResidentDiskTotal neededUtilisationFitMax context
PTQ1_0recommended5.5 GB5.5 GB7.2 GB33%Comfortable192K
PQ2_06.7 GB6.7 GB8.4 GB38%Comfortable192K
Cost of running Ternary Bonsai 2 27B on this machineUnited States (federal) · C corporation · 8h/day
Monthly economic cost
$26
Calculated after tax
Codex/Claude Code
$100/mo
≈ $100/mo · local is $74 less
Net cash at purchase
$1,981
Calculated VAT not reclaimable
Total over 5 years
$1,578
Calculated after tax, after resale
Cost per USD/1M tokens
—
Calculated

The $100 comparison uses the Codex Pro 5x / Claude Max 5x plans. A fixed planning conversion is used for USD. This compares monthly spend only: subscriptions have usage limits, local hardware has different capabilities and constraints, and taxes or regional pricing may change the charged amount. Prices checked 7 September 2026.

Purchase-price input: $1,981 in United States (federal), tax/VAT excluded · estimated · Used market exact-match reference (converted catalogue estimate). This is the localized purchase input; the after-tax economic cost is calculated separately below.

Monthly breakdown

Depreciation
1,545 over 5 years, straight-line to a 436 residual
$25.75
Electricity
31.3 kWh/month at 0.140/kWh
$4.38
Cost of capital
4.0%/yr on 1,208 average capital employed
$4.03
Monthly cost before tax$34.16
Electricity tax shield
Running costs are deductible business expenses
−$0.92
First-year expensing
§179 (100.0%)
−$6.93
Monthly economic cost after tax$26.30

Three different numbers, deliberately

Cash cost
$1,981
Money that leaves the bank account on day one, net of reclaimable VAT.
Accounting depreciation
$25.75/month
$1,545 written down over 5 years to a $436 residual.
After-tax economic cost
$26.30/month
Depreciation plus running costs plus cost of capital, less the tax those deductions save. This is the figure to compare between machines.
Assumptions and sources (verified 2026-09-07)
VAT rate
0% Official spec
VAT recoverable
0% Official spec
Federal C-corporation estimate at the flat 21% rate. Pass-through entities should use the sole-proprietor estimate as a rougher proxy.
Effective deduction rate
21.00% Calculated
Headline marginal rate 21.00%.
Depreciation
5 years, straight-line Assumption
Residual value
$436 (22%) Assumption
Extrapolated.
Electricity
$0.140/kWh Assumption
Average power draw
178 W Calculated
Load 600 W for 20% of powered hours, idle 72 W for the rest — a machine that is on is not generating tokens the whole time.
Investment allowances
§179 100.0% Official spec
Worth $416 in total — first-year expensing that replaces later tax depreciation.
Cost of capital
$4.03/month Assumption
Federal planning estimate only, not tax advice. State and local income tax, sales/use tax and incentives are excluded. It assumes 100% business use, a Section 179 election, enough business income to use it, and that the full annual limit remains available.
Ternary Bonsai 2 27B on other hardware
HardwareDecodePriceFit
RTX 5090 workstation (1x 32 GB)121 t/s$3,332 *Comfortable
Used RTX 4090 workstation (24 GB)91.1 t/s$2,071 *Comfortable
Nearest alternatives to the RTX 3090 workstation (Ryzen 9 7950X, 64 GB)
Ternary Bonsai 2 27B on Used RTX 4090 workstation (24 GB)24 GBTernary Bonsai 2 27B on RTX 5090 workstation (1x 32 GB)32 GBTernary Bonsai 2 27B on Dual used RTX 4090 workstation (48 GB)48 GBTernary Bonsai 2 27B on Radeon AI PRO R9700 workstation (32 GB)32 GBTernary Bonsai 2 27B on Dual RTX 5090 workstation (2x 32 GB)64 GB
Compare RTX 3090 workstation (Ryzen 9 7950X, 64 GB) against Used RTX 4090 workstation (24 GB) →