Skip to content

NVIDIA RTX PRO 6000 Blackwell rental: early access

Blackwell · Server Edition (being confirmed)

We’re collecting early-access requests. We’re placing our capacity in Uzbekistan. We don’t publish prices yet. We’ll confirm availability in our reply.

RTX PRO 6000

Request RTX PRO 6000

We’ll reply with terms for your workload. Nothing to pay before the contract.

Estimate usage
Compare
Memory per GPU
96 GB GDDR7
Memory bandwidth
1.6 TB/s
GPU interconnect
PCIe 5, no NVLink

NVIDIA RTX PRO 6000 Blackwell specifications

Architecture
Blackwell
Announced
2025
Memory
96 GB
Memory type
GDDR7
Memory bandwidth
1.6 TB/s
FP32
120 TFLOPS
FP16/BF16, dense
467.8 TFLOPS
FP8, dense
935.6 TFLOPS
FP4, dense
1,871.2 TFLOPSDerived: NVIDIA’s whitepaper per-SM Tensor Core rate × the 2,430 MHz boost clock in the product brief. For the Server Edition, NVIDIA gives FP16/FP8/FP4 only as rounded 1/2/4 PFLOPS peaks, the level of sparse figures; it publishes no dense ones.
FP64
not in NVIDIA’s card specsNVIDIA’s whitepaper gives FP64 on the GB202 chip as 1/64 of FP32.
RT cores
yes
NVENC/NVDEC
NVENC 4, NVDEC 4
MIG
up to 4 instances
GPU interconnect
PCIe 5, no NVLink
Power (TDP/TGP)
up to 600 W
Form factor
Server Edition (being confirmed)

Memory is specified per GPU. Multiple GPUs have separate memory: using a larger model across them requires compatible software and model partitioning. NVLink does not make them one GPU.

Other variants: RTX PRO 6000 Blackwell Workstation Edition (opens in a new tab), RTX PRO 6000 Blackwell Max-Q Workstation Edition (opens in a new tab)

The RTX PRO 6000 form factor is still being confirmed; memory bandwidth and other specifications depend on it. Specs from NVIDIA’s official materials, checked 26 September 2026.

The RTX PRO 6000 by workload

  • Inference: LLMs up to 70B in FP8 on one GPU
  • Fine-tuning: QLoRA up to 123B, LoRA up to 32B on one GPU
  • Training from scratch: models up to 3B on one GPU
  • Rendering: scenes up to 64 GB
  • FP64 computing: not suited to this GPU

An estimate from open formulas, not a benchmark or an invoice.

Servers with the NVIDIA RTX PRO 6000 Blackwell

Server configuration (CPU, RAM, disk, network) is being confirmed.

Sizing assumption: up to 8 GPUs per server. We’ll confirm the actual configuration in our reply.

More than 8 GPUs? Discuss a cluster

Sources

Similar GPUs

  • NVIDIA H200

    141 GB HBM3e · 4.8 TB/s · NVLink

    H200 leads on 4 of 5 metrics, RTX PRO 6000 on 1. H200 has more memory bandwidth (4.8 vs 1.6 TB/⁠s) and FP8 (1,978.9 vs 935.6 TFLOPS). But RTX PRO 6000 has more FP32 (120 vs 67 TFLOPS). FP64: 34 TFLOPS on H200; not in NVIDIA’s card specs for RTX PRO 6000 (NVIDIA’s whitepaper gives 1/64 of FP32 for the GB202 chip).

  • NVIDIA B200

    180 GB HBM3e · 7.7 TB/s · NVLink

    B200 leads on 5 of 6 metrics, RTX PRO 6000 on 1. B200 has more memory bandwidth (7.7 vs 1.6 TB/⁠s) and FP16/BF16 (2,250 vs 467.8 TFLOPS). But RTX PRO 6000 has more FP32 (120 vs 75 TFLOPS). FP64: 37 TFLOPS on B200; not in NVIDIA’s card specs for RTX PRO 6000 (NVIDIA’s whitepaper gives 1/64 of FP32 for the GB202 chip).

  • NVIDIA B300

    270 GB HBM3e · 7.7 TB/s · NVLink

    B300 leads on 5 of 6 metrics, RTX PRO 6000 on 1. B300 has more FP4 (14,000 vs 1,871.2 TFLOPS) and memory bandwidth (7.7 vs 1.6 TB/⁠s). But RTX PRO 6000 has more FP32 (120 vs 75 TFLOPS).

Dense FP16/BF16 and FP8 from the H100 SXM5 column of NVIDIA’s whitepaper: for the H200, NVIDIA lists only with-sparsity figures, the same as the H100 SXM’s.

The RTX PRO 6000’s FP16, FP8 and FP4 are derived figures. Derived: NVIDIA’s whitepaper per-SM Tensor Core rate × the 2,430 MHz boost clock in the product brief. For the Server Edition, NVIDIA gives FP16/FP8/FP4 only as rounded 1/2/4 PFLOPS peaks, the level of sparse figures; it publishes no dense ones.

Request RTX PRO 6000

We’ll reply with terms for your workload. Nothing to pay before the contract.