GoogleGemma 4 E4B on NVIDIA GeForce RTX 5090
Yes — RTX 5090 runs Gemma 4 E4B excellently at Q8_0 — 167 tok/s. 32 GB VRAM with plenty of headroom.
Model Size
8B
Device VRAM
32 GB
Bandwidth
1792 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 4 E4B on NVIDIA GeForce RTX 5090 at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 167 tok/s | 50ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
8.0B model. Q8_0 8.03GB on 32GB discrete_gpu.
About Gemma 4 E4B
Gemma 4 E4B (8B) is a chat, coding, reasoning model. Gemma 4's mid-range edge model. 8B total parameters with 4.5B effective. Full multimodal: text, image, audio, and video. 52% LiveCodeBench v6 and 42.5% AIME 2026 put its reasoning and coding above most models at this size. Fits comfortably on 8 GB GPUs at Q4_K_M. Apache 2.0 licensed.
View all Gemma 4 E4B hardware options →About NVIDIA GeForce RTX 5090
NVIDIA GeForce RTX 5090 has 32 GB at 1792 GB/s. Street price: $2,199.
See all models NVIDIA GeForce RTX 5090 can run →Builds with NVIDIA GeForce RTX 5090
Estimate method: Estimated from model architecture, quantization size, and device bandwidth. Reference hardware source: huggingface.co (2026-04-04)
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.