Llama 3.3 70B on Radeon AI PRO R9700 workstation (32 GB)
70.554B on 32 GB at 644 GB/s. Hardware details · Model details
CompatibilityDoes not fit
Fits
No
Calculated Requires more than 97% of usable memory. Needs a smaller quantization or more memory.
Recommended quantization
MLX 4-bit
Calculated mlx
Memory required
43.1 GB
Calculated of 29.4 GB usable — 146%
Max practical context
0
Calculated model supports 128K
Memory budget at 8K context
Model weights ⓘ
38.4 GB Calculated
KV cache ⓘ
2.5 GB Calculated
Runtime overhead ⓘ
2.2 GB Estimated
Total required
43.1 GB Calculated
Usable memory ⓘ
29.4 GB Assumption
Headroom
-13.7 GB Calculated
No quantization in our catalogue fits this machine.
Discrete GPU: 32 GB of VRAM, of which we assume 92% is usable after driver and context overhead.
This model can be run with layers offloaded to system RAM, but decode throughput typically drops by an order of magnitude once any significant fraction of the weights crosses PCIe. We do not count offload as fitting.
PerformanceEstimated0/10
Decode (generation)
—
Estimated calculated, not measured
Prefill (prompt)
—
Estimated
TTFT at 8K
~11.4–23.7 s
Estimated time to first token
Power while generating
420 W
Measured
No throughput figures for this pairing. We do not estimate performance for a model that cannot load: a tokens-per-second number for a configuration that will never run is noise, not data. The alternatives below are machines that can actually run Llama 3.3 70B.
How the estimate is calculated
- Decode: reading 70.6B active parameters at 4.50 bits/weight takes 64.87 ms at 644 GB/s x 95% achieved efficiency.
- Prefill: 96 TFLOPS (FP16) x 2.46 calibrated against measured prefill on this platform x 32% assumed model-FLOPs utilisation, divided by 2 x 70.6B 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
| Quantization | Weights | Total needed | Utilisation | Fit | Max context |
|---|---|---|---|---|---|
MLX 4-bitrecommended | 38.4 GB | 43.1 GB | 146% | Does not fit | 0 |
Q4_K_M | 41.0 GB | 45.8 GB | 155% | Does not fit | 0 |
Q8_0 | 71.2 GB | 76.8 GB | 261% | Does not fit | 0 |
BF16 | 131.4 GB | 138.9 GB | 472% | Does not fit | 0 |
Cost of running Llama 3.3 70B 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
—
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.
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
- VAT rate: No US federal VAT · verified 2026-09-07
- Marginal tax rate: IRS Publication 542 — Corporations · verified 2026-09-07
- VAT recoverable fraction: site assumption · verified 2026-09-07
- Useful life: IRS Publication 946 — How To Depreciate Property · verified 2026-09-07
- Electricity price: Site assumption · verified 2026-09-07
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.
Llama 3.3 70B on other hardware
| Hardware | Decode | Price | Fit |
|---|---|---|---|
| Dual RTX 5090 workstation (2x 32 GB) | ~38.4–55.2 t/s | €6.499 | Comfortable |
| Quad RTX 5090 workstation (4x 32 GB) | ~32.3–46.4 t/s | €13.999 | Comfortable |
| RTX PRO 6000 Blackwell workstation (96 GB) | ~24.9–35.8 t/s | €11.499 | Comfortable |
| RTX PRO 6000 Max-Q workstation (96 GB, 300 W) | ~24.9–35.8 t/s | €11.999 | Comfortable |
| Mac Studio M5 Ultra 96 GB | ~19.7–28.3 t/s | €6.599 | Comfortable |
| Mac Studio M5 Ultra 512 GB | ~11.3–16.3 t/s | €12.599 | Comfortable |
Nearest alternatives to the Radeon AI PRO R9700 workstation (32 GB)
Llama 3.3 70B on RTX 5090 workstation (1x 32 GB)32 GBLlama 3.3 70B on Used RTX 4090 workstation (24 GB)24 GBLlama 3.3 70B on Dual used RTX 4090 workstation (48 GB)48 GBLlama 3.3 70B on Mac Studio M5 Max 36 GB36 GBLlama 3.3 70B on Dual RTX 5090 workstation (2x 32 GB)64 GB
Compare Radeon AI PRO R9700 workstation (32 GB) against RTX 5090 workstation (1x 32 GB) →
Compare Radeon AI PRO R9700 workstation (32 GB) against RTX 5090 workstation (1x 32 GB) →
Page quality score (why this page is or is not indexed)
6/13 — marked noindex. Generated pages are gated so we do not ask a search engine to rank a page with nothing computed to say. The directive is emitted in the page head via the metadata API, not in the body, so it is authoritative.
- Has a memory-fit calculation (+3)
- Has a price (+2)
- Has an ownership economics calculation (+2)
- Well connected (18 internal links) (+1)
- No benchmark or estimate
- Model does not fit and there is no measurement to explain why it is worth knowing (-2)
- Fails a hard requirement: an indexable page needs both a compatibility calculation and at least one benchmark or estimate.