GoogleGemma 3 27B on NVIDIA GeForce RTX 4080 Super
RTX 4080 Super runs Gemma 3 27B at Q3_K_M — 14 tok/s. Usable on 16 GB VRAM — see full quantization options below.
Model Size
27.23B
Device VRAM
16 GB
Bandwidth
736 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 3 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 | 14 tok/s | 600ms | ✓ Yes | Acceptable | estimated |
Notes
Q3_K_M
Q3_K_M fits. 736 GB/s bandwidth delivers acceptable throughput.
About Gemma 3 27B
Gemma 3 27B (27.23B) is a chat, coding, reasoning, multi-purpose model. Google's largest open-weight model before Gemma 4. Capable reasoning and instruction following. At 27B parameters, it sits between 8B models (too limited) and 70B models (too expensive). Wide multilingual support. Fits on 24 GB GPUs at Q4.
View all Gemma 3 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: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
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.