GoogleGemma 2 27B Instruct on NVIDIA GeForce RTX 4090
Yes — RTX 4090 handles Gemma 2 27B Instruct well at Q4_K_M — 22 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
27.23B
Device VRAM
24 GB
Bandwidth
1008 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 27B Instruct on NVIDIA GeForce RTX 4090 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 | 22 tok/s | 400ms | ✓ Yes | Good | estimated |
Notes
Q4_K_M
Q4 at 15.5GB fits well on 4090 with 8.5GB headroom. Good quality-to-speed ratio.
About Gemma 2 27B Instruct
Gemma 2 27B Instruct (27.23B) is a chat, coding, reasoning, multi-purpose model. Google's 27B model with effective knowledge distillation. Reasoning and coding at a size that fits on a single 24 GB GPU at Q4. Limited to 8K context.
View all Gemma 2 27B Instruct 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: 27B model benchmarks. Reference hardware source: github.com (2026-01-15)
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.