GoogleGemma 3 27B on NVIDIA GeForce RTX 3090
Yes — RTX 3090 handles Gemma 3 27B well at Q4_K_M — 18 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
27.23B
Device VRAM
24 GB
Bandwidth
936 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 3 27B on NVIDIA GeForce RTX 3090 at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 18 tok/s | 450ms | ✓ Yes | Good | estimated |
Notes
Q4_K_M
Q4_K_M fits with 7.7GB headroom. 936 GB/s bandwidth delivers capable performance.
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 3090
NVIDIA GeForce RTX 3090 has 24 GB at 936 GB/s. Street price: $899.
See all models NVIDIA GeForce RTX 3090 can run →Builds with NVIDIA GeForce RTX 3090
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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.