GoogleGemma 2 27B Instruct on NVIDIA RTX 4090 Laptop (150-175W)
RTX 4090 Laptop (150-175W) runs Gemma 2 27B Instruct at Q4_K_M — 10 tok/s. Usable on 16 GB VRAM — see full quantization options below.
Model Size
27.23B
Device VRAM
16 GB
Bandwidth
512 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 27B Instruct on NVIDIA RTX 4090 Laptop (150-175W) 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 | 10 tok/s | 824ms | ✓ Yes | Acceptable | estimated |
Notes
Q4_K_M
Sustained post-thermal-throttle performance. TDP-capped laptop variant.
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 RTX 4090 Laptop (150-175W)
NVIDIA RTX 4090 Laptop (150-175W) has 16 GB at 512 GB/s. Street price: $0.
See all models NVIDIA RTX 4090 Laptop (150-175W) can run →Estimate method: Community laptop benchmarks and thermal throttle reports. Reference hardware source: reddit.com (2026-03-14)
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.