NVIDIA RTX PRO 6000 Blackwell Server vs NVIDIA Tesla S1075

Comparison of NVIDIA RTX PRO 6000 Blackwell Server with 96 GB GDDR7 and 24,064 cores vs NVIDIA Tesla S1075 with 4 GB GDDR3 and 240 cores.

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Performance Rating

H200 H200
MI325X MI325X
A100 A100

NVIDIA RTX PRO 6000 Blackwell Server

NVIDIA RTX PRO 6000 Blackwell Server

MI250 MI250
Instinct MI300X Instinct MI300X
RX 7900 XTX RX 7900 XTX

NVIDIA Tesla S1075

NVIDIA Tesla S1075

Contents:

Memory ML Performance Compute Power Architecture & Compatibility ML Software Support Clocks & Performance Power Consumption Rendering Benchmarks Additional

Memory

Memory Size

96 GB 4 GB ×4 (16 ГБ)

Memory Type

GDDR7 GDDR3

Memory Bandwidth

1.79 TB/s 102.4 GB/s ×4 (409.6 GB/s)

Memory Bus Width

512 бит 512 бит ×4 (2048 бит)

ML Performance

FP16 (Half Precision)

126.0 TFLOPS No

BF16 (Brain Float)

No No

TF32 (TensorFloat)

No No

Compute Power

FP32 (Single Precision)

126.0 TFLOPS 0.6221 TFLOPS

FP64 (Double Precision)

1.968 TFLOPS 0.0778 TFLOPS

CUDA Cores

24,064 240 ×4 (960)

RT Cores

188 No

Architecture & Compatibility

GPU Architecture

Blackwell 2.0 Tesla 2.0

SM (Streaming Multiprocessor)

188 30

PCIe Version

PCIe 5.0 x16 PCIe 2.0 x16

ML Software Support

CUDA Version

🔥 12.0
1.3

Clocks & Performance

Base Clock

1,590 No

Boost Clock

2,617 No

Memory Clock

1,750 800

Power Consumption

TDP/TGP

🔥 -25% 600 W
800 W

Recommended PSU

🔥 -17% 1000 W
1200 W

Power Connector

1x 16-pin No

Rendering

Texture Units (TMU)

752 80 ×4 (320)

ROP

188 No

L2 Cache

128 MB 256 KB

Benchmarks

MLPerf, llama2-70b-99.9 (fp4)

3 250 tokens/s

MLPerf, llama3.1-8b (fp4)

5 758 tokens/s

Geekbench AI, FP16

53 322 points

Geekbench AI, INT8

28 264 points

Geekbench AI, FP32

37 299 points

MLPerf, mixtral-8x7b (fp8)

3 767 tokens/s

Additional

Slots

Dual-slot Dual-slot

Release Date

March 18, 2025 June 1, 2008

Display Outputs

4x DisplayPort 2.1b
No outputs

Renting is cheaper than buying