QwenQwen3-30B-A3B on NVIDIA GeForce RTX 4090
Yes — RTX 4090 handles Qwen3-30B-A3B well at Q5_K_M — 25 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
30B
Device VRAM
24 GB
Bandwidth
1008 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen3-30B-A3B on NVIDIA GeForce RTX 4090 at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 25 tok/s | 434ms | ✓ Yes | Good | estimated |
Notes
Q5_K_M
Estimated from qwq-32b benchmarks. MoE architecture improves throughput vs. dense equivalent.
About Qwen3-30B-A3B
Qwen3-30B-A3B (30B) is a chat, coding, ai coding, reasoning, multi-purpose model. Mixture-of-Experts architecture with ~3B active parameters per token and ~30B total; inference still loads the full expert pool for typical local stacks, so VRAM tracks total model size while compute per token stays efficient. High efficiency for its quality tier. Apache 2.0; 32K default and 128K max context.
View all Qwen3-30B-A3B 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: Estimated from comparable model benchmarks. Reference hardware source: github.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.