Qwen3 8B on NVIDIA DGX Station GB300 (748 GB)
8.191B on 748 GB at 7,100 GB/s. Hardware details · Model details
Yes. Qwen3 8B fits on NVIDIA DGX Station GB300 (748 GB) at the recommended
Q8_0 configuration, requiring approximately 10.6 GB at 8K context. Practical context capacity is 40K. Expected decode for the recommended configuration is ~89.4–129 t/s. EstimatedCompatibilityComfortable
Calculated fit
Yes
Calculated Uses under 80% of usable memory. Room for a long context and other work.
Recommended quantization
Q8_0
Calculated gguf
Memory required
10.6 GB
Calculated of 635.8 GB usable — 2%
Max practical context
40K
Calculated model supports 40K
Memory budget at 8K context
Model weights ⓘ
8.3 GB Calculated
KV cache ⓘ
1.1 GB Calculated
Runtime overhead ⓘ
1.2 GB Estimated
Total required
10.6 GB Calculated
Headroom ⓘ
625.2 GB Calculated
Highest-precision quantization that leaves headroom: uses 2% of usable memory at 8K context.
Unified memory: weights, KV cache and the OS share the same 748 GB pool. We assume 85% is addressable by the GPU, which matches a headless machine with the wired-memory limit raised.
Performance
Estimated performance · recommended Q8_0
Decode, prefill and TTFT below are estimates for Q8_0. We do not have a comparable Q8_0 measurement on this machine.
Estimated decode
~89.4–129 t/s
Estimated Q8_0; calculated range
Estimated prefill
~43650–90650 t/s
Estimated Q8_0; calculated range
Estimated TTFT at 8K
~0.2–0.3 s
Estimated Q8_0; calculated range
Hardware load reference
1350 W
Measured machine-level load; not this model run
How the estimate is calculated
- Decode: reading 8.2B active parameters at 8.50 bits/weight takes 8.17 ms at 7100 GB/s x 15% achieved efficiency.
- Prefill: 2500 TFLOPS (FP16) x 2 for native FP8 tensor cores x 22% assumed model-FLOPs utilisation, divided by 2 x 8.2B 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
| Quantization | Resident | Disk | Total needed | Utilisation | Fit | Max context |
|---|---|---|---|---|---|---|
Q4_K_M | 4.8 GB | 4.8 GB | 7.0 GB | 1% | Comfortable | 40K |
Q5_K_M | 5.6 GB | 5.6 GB | 7.9 GB | 1% | Comfortable | 40K |
Q8_0recommended | 8.3 GB | 8.3 GB | 10.6 GB | 2% | Comfortable | 40K |
BF16 | 15.3 GB | 15.3 GB | 17.8 GB | 3% | Comfortable | 40K |
Cost of running Qwen3 8B on this machineUnited States (federal) · C corporation · 8h/day
Monthly economic cost
$1,182
Calculated after tax
Codex/Claude Code
$100/mo
≈ $100/mo · local is $1,082 more
Net cash at purchase
$90,082
Calculated VAT not reclaimable
Total over 5 years
$70,927
Calculated after tax, after resale
Cost per USD/1M tokens
$85.56
Calculated 13.8M 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.
Purchase-price input: $90,082 in United States (federal), tax/VAT excluded · estimated · NVIDIA DGX Station partner (converted catalogue estimate). This is the localized purchase input; the after-tax economic cost is calculated separately below.
Monthly breakdown
| Depreciation 79,272 over 5 years, straight-line to a 10,810 residual | $1,321.20 |
| Electricity 72.9 kWh/month at 0.140/kWh | $10.20 |
| Cost of capital 4.0%/yr on 50,446 average capital employed | $168.15 |
| Monthly cost before tax | $1,499.55 |
| Electricity tax shield Running costs are deductible business expenses | −$2.14 |
| First-year expensing §179 (100.0%) | −$315.29 |
| Monthly economic cost after tax | $1,182.12 |
Three different numbers, deliberately
Cash cost
$90,082
Money that leaves the bank account on day one, net of reclaimable VAT.
Accounting depreciation
$1,321.20/month
$79,272 written down over 5 years to a $10,810 residual.
After-tax economic cost
$1,182.12/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
$10,810 (12%) Assumption
Extrapolated.
Electricity
$0.140/kWh Assumption
Average power draw
414 W Calculated
Load 1350 W for 20% of powered hours, idle 180 W for the rest — a machine that is on is not generating tokens the whole time.
Investment allowances
§179 100.0% Official spec
Worth $18,917 in total — first-year expensing that replaces later tax depreciation.
Cost of capital
$168.15/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
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
1.2 t/s
Calculated purchase price only
Decode per $100/month
9.2 t/s
Calculated after-tax ownership cost
Tokens per joule
0.26
Calculated same as tokens/s per watt
USD per 1M output tokens
$85.56
Calculated at 20% utilisation
Local versus hosted APIs
| Hosted model | USD/1M output | Break-even | API at your volume | Verdict | Comparison type |
|---|---|---|---|---|---|
| Qwen3.8 Flash Alibaba Cloud | $0.42 | 767.6M/mo | $21 | API cheaper | Different model |
| DeepSeek-V4.1 Flash DeepSeek | $0.60 | 656.7M/mo | $25 | API cheaper | Different model |
| DeepSeek-V4 Pro DeepSeek | $1.98 | 162.8M/mo | $100 | API cheaper | Different model |
| DeepSeek V4 Pro (Together) Together AI | $4.40 | 55.8M/mo | $293 | API cheaper | Different model |
| GLM-5.3 Z.ai | $4.40 | 75.8M/mo | $216 | API cheaper | Different model |
| Claude Haiku 4.5 Anthropic | $5.00 | 90.9M/mo | $180 | API cheaper | Different 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 $1,182/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.
Qwen3 8B on other hardware
| Hardware | Decode | Price | Fit |
|---|---|---|---|
| NVIDIA DGX H200 (8x H200, 1,128 GB) | ~477–687 t/s | $359,430 * | Comfortable |
| Quad RTX 5090 workstation (4x 32 GB) | ~196–282 t/s | $12,611 * | Comfortable |
| Lenovo ThinkStation PX (4x RTX PRO 6000, 384 GB) | ~176–254 t/s | $58,553 * | Comfortable |
| Dual RTX 5090 workstation (2x 32 GB) | ~142–204 t/s | $5,854 * | Comfortable |
| Dell Precision 7960 Rack (2x RTX PRO 6000, 192 GB) | ~132–190 t/s | $36,663 * | Comfortable |
| RTX 5090 workstation (1x 32 GB) | ~118–170 t/s | $3,332 * | Comfortable |
Nearest alternatives to the NVIDIA DGX Station GB300 (748 GB)
Qwen3 8B on Mac Studio M5 Ultra 512 GB512 GBQwen3 8B on Mac Studio M3 Ultra 512 GB512 GBQwen3 8B on NVIDIA DGX H200 (8x H200, 1,128 GB)1,128 GBQwen3 8B on Mac Studio M5 Ultra 256 GB256 GBQwen3 8B on Mac Studio M3 Ultra 256 GB256 GB
Compare NVIDIA DGX Station GB300 (748 GB) against Mac Studio M5 Ultra 512 GB →
Compare NVIDIA DGX Station GB300 (748 GB) against Mac Studio M5 Ultra 512 GB →