GoogleGemma 2 27B Instruct on AMD Radeon RX 7900 XTX
Yes — AMD Radeon RX 7900 XTX handles Gemma 2 27B Instruct well at Q4_K_M — 19 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
27.23B
Device VRAM
24 GB
Bandwidth
960 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 2 27B Instruct on AMD Radeon RX 7900 XTX 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 | 19 tok/s | 465ms | ✓ Yes | Good | estimated |
Notes
Q4_K_M
ROCm can run large models well on RDNA 3, though CUDA equivalents still have broader tooling support. Q4_K_M fits in VRAM on this card.
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 AMD Radeon RX 7900 XTX
AMD Radeon RX 7900 XTX has 24 GB at 960 GB/s. Street price: $849.
See all models AMD Radeon RX 7900 XTX can run →Builds with AMD Radeon RX 7900 XTX
Estimate method: Estimated from rtx-4090 compatibility patterns plus ROCm/Vulkan adjustments. Reference hardware source: github.com (2026-03-26)
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.