Autor: Jakub Rusinowski · Ostatnia aktualizacja: 22 kwietnia 2026
Model library → Qwen 3.6 → Qwen 3.6 27B
Dense successor to Qwen 3.5 27B with the same hybrid Gated DeltaNet/attention architecture (64 layers) but improved coding benchmarks. Fits a single RTX 3090/4090 at Q4_K_M (~16.8 GB). Apache 2.0, ~256K context extensible to ~1M.
Qwen 3.6 27B needs about 18 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
| Parameters | 27.8 Billion |
| Context window | 262,144 |
| Architecture | Dense Transformer (Gated DeltaNet hybrid) |
| Provider | Alibaba Cloud |
| Licence | Apache 2.0 |
| Specified at | Q4_K_M |
| System RAM | 32 GB |
| Record updated | 2026-04-22 |
Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.
Modelled on a reference NVIDIA RTX 4090 (24 GB). Weights plus framework overhead only — this model publishes no architecture we can read, so no KV cache is included. A real session needs more; the figure is a floor, not a target. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.
| Quant | Bits/weight | Weights | VRAM needed | Est. speed | Fit on 24 GB |
|---|---|---|---|---|---|
| Q2_K | 2.63 | 9.1 GB | 9.9 GB | ~65 tok/s (est.) | Fits comfortably |
| Q3_K_M | 3.41 | 11.8 GB | 12.6 GB | ~52 tok/s (est.) | Fits comfortably |
| Q4_K_M | 4.83 | 16.8 GB | 17.6 GB | ~39 tok/s (est.) | Fits comfortably |
| Q5_K_M | 5.67 | 19.7 GB | 20.5 GB | ~34 tok/s (est.) | Fits comfortably |
| Q6_K | 6.56 | 22.8 GB | 23.6 GB | ~30 tok/s (est.) | Tight fit |
| Q8_0 | 8.50 | 29.5 GB | 30.3 GB | ~4 tok/s (est.) | Offloads to system RAM (slow) |
| F16 | 16.00 | 55.6 GB | 56.4 GB | — | Won't fit |
Want to set your own context length and KV-cache quantization? Use the interactive VRAM calculator.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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The cheapest catalogued GPU that runs Qwen 3.6 27B is the AMD Radeon RX 7900 XT (20 GB).
Install Ollama, then run:
ollama run qwen3.6:27bWeights on Hugging Face: Qwen/Qwen3.6-27B.
Best for: reasoning, coding, multilingual, long documents.
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