RTX PRO Blackwell variants guide

NVIDIA’s RTX PRO Blackwell lineup spans 4 VRAM tiers (24 GB to 96 GB) and 3 form factors (Workstation, Max-Q, Server), plus a China export-compliance variant. This guide explains the differences so you pick the right SKU for your workload.

​

The RTX PRO Blackwell lineup

​

Form factor decision tree

​

Workstation (full tower)

RTX PRO 6000 Workstation is the flagship: 96 GB GDDR7 in a standard full-tower chassis with active cooling and display outputs. When to choose:

• You need maximum single-GPU VRAM (96 GB) for 120B MoE models at FP8
• You have a standard workstation tower with adequate cooling
• You need display outputs for interactive work
• Budget is ~$16,000 per card

Example use cases:

• Serving DeepSeek V4-Flash-0731 (162-167 GB) on 2x PRO 6000 Workstation (192 GB total)
• Running GLM-4.5-Air (106B MoE) at FP8 on a single card
• Multi-user team serving with 70B models at high precision

​

Max-Q (low-profile, 4x per chassis)

RTX PRO 6000 Max-Q is the density play: same 96 GB GDDR7 as the Workstation variant, but in a low-profile form factor that fits 4 cards in a single workstation chassis. When to choose:

• You need 384 GB total VRAM in one machine (4x 96 GB)
• You’re running frontier models like DeepSeek V4.1 Flash (763B total params) at high precision
• You have a workstation chassis designed for 4x low-profile GPUs
• Budget is ~$8,500 per card (cheaper than Workstation variant)

Example use cases:

• 4x RTX PRO 6000 Max-Q (384 GB total) runs DeepSeek V4.1 Flash at FP8+MXFP4 with ~135 tok/s per GPU
• High-density inference server for multiple 70B models
• Research workloads that need 300+ GB VRAM without clustering multiple nodes

​

Server (rack-mount, datacenter)

RTX PRO 6000 Server is identical to the Workstation variant in specs, but designed for rack-mount chassis with datacenter cooling (no active fans on the card, relies on chassis airflow). When to choose:

• You’re building a rack-mount inference server
• Your datacenter provides forced-air cooling
• You need high-density deployment (multiple cards per 2U/4U chassis)
• You don’t need display outputs

Example use cases:

• Multi-tenant inference API serving
• Enterprise LLM deployments with SLA requirements
• Clusters of 8-16 cards for large-scale model serving

​

RTX 6000D (China export-compliance)

RTX 6000D is a cut-down RTX PRO 6000 for the China market. It has 84 GB GDDR7 instead of 96 GB, with ~12% lower bandwidth and performance. When to choose:

• You’re in China or selling to China-based customers
• You need to comply with U.S. export controls on advanced AI hardware
• 84 GB is sufficient for your workload (still fits 120B MoE at Q4)

Example use cases:

• Same as RTX PRO 6000 Workstation, but with 12 GB less VRAM
• 2x RTX 6000D (168 GB total) runs DeepSeek V4-Flash-0731 with less headroom than 2x PRO 6000

​

RTX PRO 4000 / 4500 / 5000: Mid-tier professional cards

Not every workload needs 96 GB. The mid-tier RTX PRO cards offer professional features (ECC memory, ISV certifications, professional drivers) at lower price points.

​

RTX PRO 4000 (24 GB, ~$2,000-2,500)

Best for: 30B models at Q4, 14B models at FP16 Example workloads:

• Qwen3.6-35B-A3B (35B MoE, 3B active) at Q4: ~75 tok/s
• Llama 3.1 14B at FP16: ~75 tok/s
• Gemma 4 E4B at Q8: ~100 tok/s

When to choose over RTX 4090:

• You need ECC memory for production serving
• You need ISV certifications for professional software
• You need professional drivers with longer support lifecycle
• You need 24/7 reliability guarantees

​

RTX PRO 4500 (32 GB, ~$3,000-4,000)

Best for: 70B models at Q4, 32B dense models at FP16 Example workloads:

• Qwen3 70B at Q4: ~85 tok/s
• Llama 3.1 32B at FP16: ~85 tok/s
• 2x RTX PRO 4500 (64 GB total) runs 120B MoE models with tensor parallelism

When to choose over RTX 5090:

• Same 32 GB VRAM as RTX 5090, but with professional features
• ~15% slower than RTX 5090 on raw inference speed, but with ECC and ISV support
• Better for production deployments where reliability matters more than peak speed

​

RTX PRO 5000 (48 GB or 72 GB, ~$5,000-7,000)

Best for: 70B models at FP8, 120B MoE models at Q4 Example workloads:

• Qwen3 70B at FP8: ~100 tok/s (higher quality than Q4)
• Qwen3.5-122B-A10B (122B MoE) at Q4: ~30 tok/s
• GLM-4.5-Air (106B MoE) at Q4: ~35 tok/s

When to choose:

• You need 48-72 GB VRAM for 70B models at FP8 (better quality than Q4)
• You’re running 120B MoE models that don’t fit in 32 GB
• You need professional features but can’t afford 96 GB PRO 6000

48 GB vs 72 GB variant:

• 48 GB: Fits 70B FP8 with ~8 GB headroom for KV cache
• 72 GB: Fits 70B FP8 with ~32 GB headroom, or 120B MoE at higher quantization

​

Multi-GPU configurations

RTX PRO cards shine in multi-GPU setups. Here are common configurations:

​

2x RTX PRO 6000 (192 GB total)

Best for: DeepSeek V4-Flash-0731 (162-167 GB), GLM-5.2 at Q4 Performance:

• DeepSeek V4-Flash-0731 at FP8+MXFP4: ~106-210 tok/s (community-reported range)
• GLM-5.2 at Q4: ~26 tok/s (estimated, needs validation)

Requirements:

• Workstation chassis with 2x full-length PCIe 5.0 x16 slots
• 2x 300W PCIe power connectors (or 12VHPWR)
• NVLink bridge recommended for tensor parallelism (RTX PRO 6000 supports NVLink)

​

4x RTX PRO 6000 Max-Q (384 GB total)

Best for: DeepSeek V4.1 Flash (763B total params) at high precision Performance:

• DeepSeek V4.1 Flash at FP8 dense + MXFP4 experts: ~135 tok/s per GPU (540 tok/s aggregate)
• Multiple 70B models simultaneously

Requirements:

• Workstation chassis designed for 4x low-profile GPUs
• 4x 250W PCIe power connectors (1,000W total)
• High-airflow cooling (4x cards generate significant heat)

​

2x RTX PRO 4500 (64 GB total)

Best for: 120B MoE models at Q4, cost-effective alternative to 2x PRO 6000 Performance:

• Qwen3.5-122B-A10B at Q4: ~40-50 tok/s (estimated)
• GLM-4.5-Air at Q4: ~45 tok/s (estimated)

Requirements:

• Workstation chassis with 2x full-length PCIe 5.0 x16 slots
• 2x 200W PCIe power connectors
• NVLink bridge recommended (RTX PRO 4500 supports NVLink)

​

Professional features vs consumer cards

Why pay 2-3x more for RTX PRO over RTX 5090?

​

Pricing and availability

​

Runtime compatibility

All RTX PRO Blackwell cards have full CUDA support and work with all major inference backends:

​

Next steps