Gemma 3 27B on Radeon AI PRO R9700 workstation (32 GB)

27.432B on 32 GB at 644 GB/s. Hardware details · Model details

CompatibilityComfortable
Fits
Yes
Calculated Uses under 80% of usable memory. Room for a long context and other work.
Recommended quantization
Q4_K_M
Calculated gguf
Memory required
21.3 GB
Calculated of 29.4 GB usable — 72%
Max practical context
16K
Calculated model supports 128K

Memory budget at 8K context

Model weights
16.0 GB Calculated
KV cache
3.9 GB Calculated
Runtime overhead
1.5 GB Estimated
Total required
21.3 GB Calculated
Usable memory
29.4 GB Assumption
Headroom
8.1 GB Calculated
Highest-precision quantization that leaves headroom: uses 72% of usable memory at 8K context.
Discrete GPU: 32 GB of VRAM, of which we assume 92% is usable after driver and context overhead.
PerformanceEstimated0/10
Decode (generation)
~29.3–42.2 t/s
Estimated calculated, not measured
Prefill (prompt)
~896–1860 t/s
Estimated
TTFT at 8K
~4.5–9.3 s
Estimated time to first token
Power while generating
420 W
Measured 0.30 tokens/s per watt
These figures are estimated, not measured. Nobody has published a benchmark of Gemma 3 27B on this machine that we know of, so we calculate throughput from memory bandwidth and active parameter count. Estimates are always shown as a range. Expand the working below to see exactly how the number was produced.
How the estimate is calculated
  1. Decode: reading 27.4B active parameters at 4.85 bits/weight takes 27.18 ms at 644 GB/s x 95% achieved efficiency.
  2. Prefill: 96 TFLOPS (FP16) x 2.46 calibrated against measured prefill on this platform 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.

This model at other quantizations on this machine
QuantizationWeightsTotal neededUtilisationFitMax context
MLX 4-bit14.9 GB20.3 GB69%Comfortable16K
Q4_K_Mrecommended16.0 GB21.3 GB72%Comfortable16K
Q8_027.7 GB33.4 GB113%Does not fit0
BF1651.1 GB57.5 GB195%Does not fit0
Cost of running Gemma 3 27B on this machineUnited States (federal) · C corporation · 8h/day
Monthly economic cost
$34
Calculated after tax
Codex/Claude Code
$100/mo
≈ $100/mo · local is $66 less
Net cash at purchase
$2,521
Calculated VAT not reclaimable
Total over 5 years
$2,044
Calculated after tax, after resale
Cost per USD/1M tokens
$7.52
Calculated 4.5M tokens/month

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.

Monthly breakdown

Depreciation
2,143 over 5 years, straight-line to a 378 residual
$35.72
Electricity
21.1 kWh/month at 0.140/kWh
$2.96
Cost of capital
4.0%/yr on 1,450 average capital employed
$4.83
Monthly cost before tax$43.51
Electricity tax shield
Running costs are deductible business expenses
−$0.62
First-year expensing
§179 (100.0%)
−$8.82
Monthly economic cost after tax$34.06

Three different numbers, deliberately

Cash cost
$2,521
Money that leaves the bank account on day one, net of reclaimable VAT.
Accounting depreciation
$35.72/month
$2,143 written down over 5 years to a $378 residual.
After-tax economic cost
$34.06/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
$378 (15%) Assumption
Two GPU generations later, the card is worth a fraction of its list price.
Electricity
$0.140/kWh Assumption
Average power draw
120 W Calculated
Load 420 W for 20% of powered hours, idle 45 W for the rest — a machine that is on is not generating tokens the whole time.
Investment allowances
§179 100.0% Official spec
Worth $529 in total — first-year expensing that replaces later tax depreciation.
Cost of capital
$4.83/month Assumption
Assumes the machine generates tokens 20% of its 176 powered hours per month. Cost per token scales inversely with this number — halve the utilisation and the cost per token doubles.
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.
Efficiency metrics
Decode per $1,000 spent
14.2 t/s
Calculated purchase price only
Decode per $100/month
104.9 t/s
Calculated after-tax ownership cost
Tokens per joule
0.30
Calculated same as tokens/s per watt
USD per 1M output tokens
$7.52
Calculated at 20% utilisation
Local versus hosted APIs
Hosted modelUSD/1M outputBreak-evenAPI at your volumeVerdictComparison type
Qwen3.8 Flash
Alibaba Cloud
$0.4222.1M/mo$7API cheaperDifferent model
DeepSeek-V4 Flash
DeepSeek
$0.6614.1M/mo$11API cheaperDifferent model
DeepSeek-V4 Pro
DeepSeek
$1.984.7M/mo$33About equalDifferent model
DeepSeek V4 Pro (Together)
Together AI
$4.401.6M/mo$96Local cheaperDifferent model
GLM-5.3
Z.ai
$4.402.2M/mo$71Local cheaperDifferent model
Claude Haiku 4.5
Anthropic
$5.002.6M/mo$59Local cheaperDifferent model
Different-model comparison: the hosted model is not the model you would run locally. Treat this as a workload-quality trade-off, not a direct economic equivalence — the frontier model may complete a task in fewer tokens, or complete tasks the local model cannot. Break-even is the monthly output volume at which API spend equals the $34/month economic cost of owning this machine, assuming 8 input tokens per output token. Hosted prices are published in USD. This table is the canonical US default.
Page quality score (why this page is or is not indexed)

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