GoogleGemma 4 E4B on NVIDIA GeForce RTX 5080
Yes — RTX 5080 runs Gemma 4 E4B excellently at Q8_0 — 89 tok/s. 16 GB VRAM with plenty of headroom.
Model Size
8B
Device VRAM
16 GB
Bandwidth
960 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 4 E4B on NVIDIA GeForce RTX 5080 at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 89 tok/s | 50ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
8.0B model. Q8_0 8.03GB on 16GB 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 5080
NVIDIA GeForce RTX 5080 has 16 GB at 960 GB/s. Street price: $1,099.
See all models NVIDIA GeForce RTX 5080 can run →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.