QwenQwen3.6-27B on NVIDIA GeForce RTX 4090
Yes — RTX 4090 handles Qwen3.6-27B well at Q5_K_M — 40 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
27B
Device VRAM
24 GB
Bandwidth
1008 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen3.6-27B on NVIDIA GeForce RTX 4090 at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 40 tok/s | 250ms | ✓ Yes | Good | estimated |
Notes
Q5_K_M
Good quality Q5_K_M (19GB, 5GB headroom). Qwen 3.6 dense 27B; VRAM slightly above Qwen 3.5-27B.
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 GeForce RTX 4090
NVIDIA GeForce RTX 4090 has 24 GB at 1008 GB/s. Street price: $1,799.
See all models NVIDIA GeForce RTX 4090 can run →Builds with NVIDIA GeForce RTX 4090
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.