MetaLlama 4 Scout on NVIDIA RTX PRO 6000 Blackwell
Yes — RTX PRO 6000 Blackwell runs Llama 4 Scout excellently at Q5_K_M — 95 tok/s. 96 GB VRAM with plenty of headroom.
Model Size
109B
Device VRAM
96 GB
Bandwidth
1800 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Llama 4 Scout on NVIDIA RTX PRO 6000 Blackwell 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 | 95 tok/s | 40ms | ✓ Yes | Excellent | estimated |
Notes
Q5_K_M
96 GB GDDR7 fits Q5_K_M (75 GB) with 21 GB headroom. 1.8 TB/s bandwidth. High quality quantization with good speed.
About Llama 4 Scout
Llama 4 Scout (109B) is a chat, reasoning, multi-purpose model. Large MoE model (~109B total, ~17B active per token; 16 experts, 2 active). Multimodal (text and image) with an enormous advertised context window (10M tokens); practical local runs are usually capped by VRAM and tooling far below that. MoE loads the full weight set for common local inference paths. Not a consumer GPU model: even Q4_K_M needs ~60GB VRAM. Expect H100-class or dual A100 hardware for practical deployment. Do not recommend to RTX 4090 or Mac users.
View all Llama 4 Scout hardware options →About NVIDIA RTX PRO 6000 Blackwell
NVIDIA RTX PRO 6000 Blackwell has 96 GB at 1800 GB/s. Street price: $7,500.
See all models NVIDIA RTX PRO 6000 Blackwell can run →Estimate method: Estimated from bandwidth ratio vs RTX 4090 (1800/1008 = 1.78x) with conservative margin. Reference hardware source: nvidia.com (2026-03-29)
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.