Qwen3.6 27B on Dual RTX 5090 workstation (2x 32 GB)

27.781B on 64 GB at 3,584 GB/s. Hardware details · Model details

Run locally →
Yes. Qwen3.6 27B fits on Dual RTX 5090 workstation (2x 32 GB) at the recommended Q8_0 configuration, requiring approximately 30.8 GB at 8K context. Practical context capacity is 256K. Expected decode for the recommended configuration is ~50.4–72.6 t/s. Estimated
CompatibilityComfortable
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
30.8 GB
Calculated of 56.3 GB usable — 55%
Max practical context
256K
Calculated model supports 256K

Memory budget at 8K context

Model weights ⓘ
28.0 GB Calculated
KV cache ⓘ
0.5 GB Calculated
Runtime overhead ⓘ
2.2 GB Estimated
Total required
30.8 GB Calculated
Headroom ⓘ
25.5 GB Calculated
Highest-precision quantization that leaves headroom: uses 55% of usable memory at 8K context.
2 GPUs providing 64 GB aggregate VRAM. Assumes tensor- or layer-parallel sharding; each GPU carries its own context and communication buffers.
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.
Multi-GPU throughput depends heavily on interconnect. Without NVLink or NVSwitch, tensor parallelism over PCIe adds latency that partially offsets the extra bandwidth.
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
~50.4–72.6 t/s
Estimated Q8_0; calculated range
Estimated prefill
~1800–3750 t/s
Estimated Q8_0; calculated range
Estimated TTFT at 8K
~2.2–4.7 s
Estimated Q8_0; calculated range
Hardware load reference
1180 W
Measured machine-level load; not this model run
How the estimate is calculated
  1. Multi-GPU: 1792 GB/s per card, with each additional card contributing 40% of its bandwidth — 2509 GB/s effective, not the 3584 GB/s aggregate. Cross-GPU collectives use PCIe rather than a dedicated GPU fabric.
  2. Decode: reading 27.8B active parameters at 8.50 bits/weight takes 14.86 ms at 2509 GB/s x 79% achieved efficiency.
  3. Prefill: 419 TFLOPS (FP16) x 2 for native FP8 tensor cores x 0.71 calibrated against measured prefill on this platform x 26% assumed model-FLOPs utilisation, divided by 2 x 27.8B 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
Q4_K_M16.2 GB16.2 GB18.5 GB33%Comfortable256K
Q5_K_M19.0 GB19.0 GB21.4 GB38%Comfortable256K
Q8_0recommended28.0 GB28.0 GB30.8 GB55%Comfortable256K
BF1651.7 GB51.7 GB55.2 GB98%Does not fit0
Cost of running Qwen3.6 27B on this machineUnited States (federal) · C corporation · 8h/day
Monthly economic cost
$80
Calculated after tax
Codex/Claude Code
$100/mo
≈ $100/mo · local is $20 less
Net cash at purchase
$5,854
Calculated VAT not reclaimable
Total over 5 years
$4,799
Calculated after tax, after resale
Cost per USD/1M tokens
$10.26
Calculated 7.8M 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: $5,854 in United States (federal), tax/VAT excluded · estimated · NL retail (system build) (converted catalogue estimate). This is the localized purchase input; the after-tax economic cost is calculated separately below.

Monthly breakdown

Depreciation
4,976 over 5 years, straight-line to a 878 residual
$82.94
Electricity
57.0 kWh/month at 0.140/kWh
$7.98
Cost of capital
4.0%/yr on 3,366 average capital employed
$11.22
Monthly cost before tax$102.14
Electricity tax shield
Running costs are deductible business expenses
−$1.68
First-year expensing
§179 (100.0%)
−$20.49
Monthly economic cost after tax$79.98

Three different numbers, deliberately

Cash cost
$5,854
Money that leaves the bank account on day one, net of reclaimable VAT.
Accounting depreciation
$82.94/month
$4,976 written down over 5 years to a $878 residual.
After-tax economic cost
$79.98/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
$878 (15%) Assumption
Two GPU generations later, the card is worth a fraction of its list price.
Electricity
$0.140/kWh Assumption
Average power draw
324 W Calculated
Load 1180 W for 20% of powered hours, idle 110 W for the rest — a machine that is on is not generating tokens the whole time.
Investment allowances
§179 100.0% Official spec
Worth $1,229 in total — first-year expensing that replaces later tax depreciation.
Cost of capital
$11.22/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
10.5 t/s
Calculated purchase price only
Decode per $100/month
76.9 t/s
Calculated after-tax ownership cost
Tokens per joule
0.19
Calculated same as tokens/s per watt
USD per 1M output tokens
$10.26
Calculated at 20% utilisation
Local versus hosted APIs
Hosted modelUSD/1M outputBreak-evenAPI at your volumeVerdictComparison type
Qwen3.8 Flash
Alibaba Cloud
$0.4251.9M/mo$12API cheaperDifferent model
DeepSeek-V4.1 Flash
DeepSeek
$0.6044.4M/mo$14API cheaperDifferent model
DeepSeek-V4 Pro
DeepSeek
$1.9811.0M/mo$57API cheaperDifferent model
DeepSeek V4 Pro (Together)
Together AI
$4.403.8M/mo$165Local cheaperDifferent model
GLM-5.3
Z.ai
$4.405.1M/mo$122Local cheaperDifferent model
Claude Haiku 4.5
Anthropic
$5.006.2M/mo$101Local 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 $80/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.