MicrosoftPhi-3 Medium 14B Instruct on NVIDIA RTX PRO 6000 Blackwell Max-Q
Yes — RTX PRO 6000 Blackwell Max-Q handles Phi-3 Medium 14B Instruct well at Q8_0 — 64 tok/s. Solid daily-driver performance on 96 GB VRAM.
Model Size
14B
Device VRAM
96 GB
Bandwidth
1800 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-3 Medium 14B Instruct on NVIDIA RTX PRO 6000 Blackwell Max-Q at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 64 tok/s | 126ms | ✓ Yes | Good | estimated |
Notes
Q8_0
96 GB GDDR7 fits Q8_0 (15.2 GB) with 81 GB headroom. 1.8 TB/s bandwidth. Near-FP16 quality — minimal quantization loss.
About Phi-3 Medium 14B Instruct
Phi-3 Medium 14B Instruct (14B) is a chat, coding, reasoning, multi-purpose model. 14B model with capable reasoning and coding performance. Fits comfortably on 16 GB GPUs at Q4 and excels at structured output tasks. MIT license makes it attractive for commercial use.
View all Phi-3 Medium 14B Instruct hardware options →About NVIDIA RTX PRO 6000 Blackwell Max-Q
NVIDIA RTX PRO 6000 Blackwell Max-Q has 96 GB at 1800 GB/s. Street price: $7,000.
See all models NVIDIA RTX PRO 6000 Blackwell Max-Q can run →Estimate method: Estimated from full RTX PRO 6000 with ~8% reduction for Max-Q 300W power envelope. 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.