Qwen3.6 27B on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
27.781B on 128 GB at 256 GB/s. Hardware details · Model details
Yes. Qwen3.6 27B fits on Framework Desktop (Ryzen AI Max+ 395, 128 GB) at the recommended
Q8_0 configuration, requiring approximately 30.4 GB at 8K context. Practical context capacity is 256K. Measured alternative: 11.50 t/s median across 1 comparable run at Q4_K_M and 4K context. MeasuredCompatibilityComfortable
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
30.4 GB
Calculated of 105.0 GB usable — 29%
Max practical context
256K
Calculated model supports 256K
Observed resident fit: Q4_K_M with eng_lm_studio at 4K context. This is measured evidence for those exact artifacts and settings; it does not change the standard memory calculation above.
Memory budget at 8K context
Model weights ⓘ
28.0 GB Calculated
KV cache ⓘ
0.5 GB Calculated
Runtime overhead ⓘ
1.8 GB Estimated
Total required
30.4 GB Calculated
Headroom ⓘ
74.6 GB Calculated
Highest-precision quantization that leaves headroom: uses 29% of usable memory at 8K context.
Unified LPDDR: the accelerator allocates from the same 128 GB pool as the OS. We assume 82% is available to the inference engine.
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 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
~3.4–4.9 t/s
Estimated Q8_0; calculated range
Estimated prefill
~124–258 t/s
Estimated Q8_0; calculated range
Estimated TTFT at 8K
~31.8–66.2 s
Estimated Q8_0; calculated range
Hardware load reference
130 W
Measured machine-level load; not this model run
Measured results · Q4_K_M
1 measured runThese are real Q4_K_M measurements. The recommendation above uses Q8_0, so they are not used to produce its estimated KPIs.
| Quant | Engine | Decode mode | Context | Runs | Median decode | Median prefill | Latest | Sources |
|---|---|---|---|---|---|---|---|---|
Q4_K_M | LM Studio | standard | 4K | 1 | 11.50 t/s | — | 10 Feb 2026 | mindstudio.ai |
How the estimate is calculated
- Decode: reading 27.8B active parameters at 8.50 bits/weight takes 239.06 ms at 256 GB/s x 48% achieved efficiency.
- Prefill: 59 TFLOPS (FP16) x 18% 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.
This model at other quantizations on this machine
| Quantization | Resident | Disk | Total needed | Utilisation | Fit | Max context |
|---|---|---|---|---|---|---|
Q4_K_M | 16.2 GB | 16.2 GB | 18.1 GB | 17% | ComfortableResident run observed | 256K |
Q5_K_M | 19.0 GB | 19.0 GB | 21.0 GB | 20% | Comfortable | 256K |
Q8_0recommended | 28.0 GB | 28.0 GB | 30.4 GB | 29% | Comfortable | 256K |
BF16 | 51.7 GB | 51.7 GB | 54.8 GB | 52% | Comfortable | 256K |
Cost of running Qwen3.6 27B on this machineUnited States (federal) · C corporation · 8h/day
Monthly economic cost
$28
Calculated after tax
Codex/Claude Code
$100/mo
≈ $100/mo · local is $72 less
Net cash at purchase
$2,161
Calculated VAT not reclaimable
Total over 5 years
$1,673
Calculated after tax, after resale
Cost per USD/1M tokens
$52.94
Calculated 0.5M 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.
Purchase-price input: $2,161 in United States (federal), tax/VAT excluded · estimated · Framework (converted catalogue estimate). This is the localized purchase input; the after-tax economic cost is calculated separately below.
Monthly breakdown
| Depreciation 1,837 over 5 years, straight-line to a 324 residual | $30.62 |
| Electricity 6.3 kWh/month at 0.140/kWh | $0.88 |
| Cost of capital 4.0%/yr on 1,243 average capital employed | $4.14 |
| Monthly cost before tax | $35.63 |
| Electricity tax shield Running costs are deductible business expenses | −$0.18 |
| First-year expensing §179 (100.0%) | −$7.56 |
| Monthly economic cost after tax | $27.89 |
Three different numbers, deliberately
Cash cost
$2,161
Money that leaves the bank account on day one, net of reclaimable VAT.
Accounting depreciation
$30.62/month
$1,837 written down over 5 years to a $324 residual.
After-tax economic cost
$27.89/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
$324 (15%) Assumption
Two GPU generations later, the card is worth a fraction of its list price.
Electricity
$0.140/kWh Assumption
Average power draw
36 W Calculated
Load 130 W for 20% of powered hours, idle 12 W for the rest — a machine that is on is not generating tokens the whole time.
Investment allowances
§179 100.0% Official spec
Worth $454 in total — first-year expensing that replaces later tax depreciation.
Cost of capital
$4.14/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
1.9 t/s
Calculated purchase price only
Decode per $100/month
14.9 t/s
Calculated after-tax ownership cost
Tokens per joule
0.12
Calculated same as tokens/s per watt
USD per 1M output tokens
$52.94
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 | 18.1M/mo | $1 | API cheaper | Different model |
| DeepSeek-V4.1 Flash DeepSeek | $0.60 | 15.5M/mo | $1 | API cheaper | Different model |
| DeepSeek-V4 Pro DeepSeek | $1.98 | 3.8M/mo | $4 | API cheaper | Different model |
| DeepSeek V4 Pro (Together) Together AI | $4.40 | 1.3M/mo | $11 | API cheaper | Different model |
| GLM-5.3 Z.ai | $4.40 | 1.8M/mo | $8 | API cheaper | Different model |
| Claude Haiku 4.5 Anthropic | $5.00 | 2.1M/mo | $7 | 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 $28/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.
Qwen3.6 27B on other hardware
| Hardware | Decode | Price | Fit |
|---|---|---|---|
| NVIDIA DGX H200 (8x H200, 1,128 GB) | ~331–476 t/s | $359,430 * | Comfortable |
| Quad RTX 5090 workstation (4x 32 GB) | ~75.5–109 t/s | $12,611 * | Comfortable |
| Lenovo ThinkStation PX (4x RTX PRO 6000, 384 GB) | ~66.1–95.1 t/s | $58,553 * | Comfortable |
| RTX 5090 workstation (1x 32 GB) | ~55.7–80.1 t/s | $3,332 * | Comfortable |
| Dual RTX 5090 workstation (2x 32 GB) | ~50.4–72.6 t/s | $5,854 * | Comfortable |
| Dell Precision 7960 Rack (2x RTX PRO 6000, 192 GB) | ~46.2–66.5 t/s | $36,663 * | Comfortable |
Nearest alternatives to the Framework Desktop (Ryzen AI Max+ 395, 128 GB)
Qwen3.6 27B on GMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)128 GBQwen3.6 27B on Framework Desktop (Ryzen AI Max+ 395, 64 GB)64 GBQwen3.6 27B on NVIDIA DGX Spark 128 GB128 GBQwen3.6 27B on Radeon AI PRO R9700 workstation (32 GB)32 GBQwen3.6 27B on Mac Studio M5 Max 128 GB128 GB
Compare Framework Desktop (Ryzen AI Max+ 395, 128 GB) against GMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB) →
Compare Framework Desktop (Ryzen AI Max+ 395, 128 GB) against GMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB) →