QwenQwen3.5-27B on NVIDIA GeForce RTX 4080 Super
RTX 4080 Super runs Qwen3.5-27B at Q3_K_M — 38 tok/s. Usable on 16 GB VRAM — see full quantization options below.
Model Size
27B
Device VRAM
16 GB
Bandwidth
736 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen3.5-27B on NVIDIA GeForce RTX 4080 Super at Q3_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 38 tok/s | 263ms | ✓ Yes | Acceptable | estimated |
Notes
Q3_K_M
Compressed Q3_K_M (14GB, 2GB headroom). Noticeable quality loss vs Q4+.
About Qwen3.5-27B
Qwen3.5-27B (27B) is a chat, coding, ai coding, reasoning, multi-purpose model. Dense 27B from the Qwen 3.5 family. Native multimodal (text, image, video). 256K context window. Competitive with Gemma 3 27B and Qwen 3 32B at lower VRAM. Apache 2.0.
View all Qwen3.5-27B hardware options →About NVIDIA GeForce RTX 4080 Super
NVIDIA GeForce RTX 4080 Super has 16 GB at 736 GB/s. Street price: $979.
See all models NVIDIA GeForce RTX 4080 Super can run →Estimate method: Estimated from Qwen 3 32B and MoE benchmarks with size/architecture scaling. Reference hardware source: github.com (2026-03-24)
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.