QwenQwen3.6-27B on NVIDIA RTX 4080 Laptop (120-150W)
RTX 4080 Laptop (120-150W) cannot run Qwen3.6-27B. 12 GB VRAM is insufficient at any quantization level.
Model Size
27B
Device VRAM
12 GB
Bandwidth
384 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen3.6-27B on NVIDIA RTX 4080 Laptop (120-150W) at Q3_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | – | – | ✗ Offload | Not viable | estimated |
Notes
Q3_K_M
Q3_K_M needs 14GB but only 12GB available. Requires CPU offloading — significantly slower. Qwen 3.6 dense 27B; VRAM slightly above Qwen 3.5-27B. Does not fit in 12GB VRAM (15GB required for Q3_K_M).
About Qwen3.6-27B
Qwen3.6-27B (27B) is a chat, coding, ai coding, reasoning, multi-purpose model. Dense 27B from the Qwen 3.6 family (April 2026). Strong coding and agentic workflows; native multimodal. 262K context window. VRAM figures include modest KV headroom at default context; long-context runs need more memory or KV cache quantization. Apache 2.0.
View all Qwen3.6-27B hardware options →About NVIDIA RTX 4080 Laptop (120-150W)
NVIDIA RTX 4080 Laptop (120-150W) has 12 GB at 384 GB/s. Street price: $0.
See all models NVIDIA RTX 4080 Laptop (120-150W) can run →Estimate method: Estimated from Qwen 3 32B and MoE benchmarks with size/architecture scaling. Reference hardware source: github.com (2026-05-26)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.