Side-by-side, with the numbers that matter.
Two rigs, one table. Higher numbers win in cobalt; TDP and price flip.
Rig A
NVIDIA H100
NVIDIA · accelerator
Change
- 1X Neo
- Agility Robotics Digit
- Alibaba Qwen2.5-72B-Instruct (Q4 quant)
- AMD Instinct MI300X
- AMD Instinct MI325X
- AMD Instinct MI355X
- Anthropic Claude Opus 4.7
- Apple Mac Pro (M2 Ultra, 2023)
- Apple Mac Studio (M3 Ultra)
- Apple MacBook Pro 16-inch, M4 Max (2024)
- Apptronik Apollo
- Aurora
- AWS Trainium2
- Boston Dynamics Atlas
- Boston Dynamics Spot
- Cerebras Wafer-Scale Engine 3
- El Capitan
- Figure 02
- Frontier (OLCF-5)
- Google Cloud TPU v5p
- Groq Language Processing Unit
- Intel Gaudi 3 HL-325L
- MSI GeForce RTX 5090 Suprim Liquid
- NVIDIA B100
- NVIDIA B200
- NVIDIA DGX B200
- NVIDIA DGX H200
- NVIDIA DGX Spark
- NVIDIA Eos DGX SuperPOD
- NVIDIA GB200
- NVIDIA GB200 NVL72
- NVIDIA GeForce RTX 4090 Founders Edition
- NVIDIA GeForce RTX 5070 Ti
- NVIDIA GeForce RTX 5080 Founders Edition
- NVIDIA GeForce RTX 5090 Founders Edition
- NVIDIA GH200 Grace Hopper
- NVIDIA H100
- NVIDIA H200
- NVIDIA HGX B200
- NVIDIA Jetson AGX Thor
- NVIDIA RTX PRO 4500 Blackwell
- NVIDIA RTX PRO 5000 Blackwell
- NVIDIA RTX PRO 6000 Blackwell
- OpenAI GPT-5
- SambaNova SN40L Reconfigurable Dataflow Unit
- Sanctuary AI Phoenix
- Tesla Optimus
- The Stargate Project
- Unitree B2
- Unitree G1
- Unitree H1
Rig B
Alibaba Qwen2.5-72B-Instruct (Q4 quant)
Alibaba · cloud-model
Change
- 1X Neo
- Agility Robotics Digit
- Alibaba Qwen2.5-72B-Instruct (Q4 quant)
- AMD Instinct MI300X
- AMD Instinct MI325X
- AMD Instinct MI355X
- Anthropic Claude Opus 4.7
- Apple Mac Pro (M2 Ultra, 2023)
- Apple Mac Studio (M3 Ultra)
- Apple MacBook Pro 16-inch, M4 Max (2024)
- Apptronik Apollo
- Aurora
- AWS Trainium2
- Boston Dynamics Atlas
- Boston Dynamics Spot
- Cerebras Wafer-Scale Engine 3
- El Capitan
- Figure 02
- Frontier (OLCF-5)
- Google Cloud TPU v5p
- Groq Language Processing Unit
- Intel Gaudi 3 HL-325L
- MSI GeForce RTX 5090 Suprim Liquid
- NVIDIA B100
- NVIDIA B200
- NVIDIA DGX B200
- NVIDIA DGX H200
- NVIDIA DGX Spark
- NVIDIA Eos DGX SuperPOD
- NVIDIA GB200
- NVIDIA GB200 NVL72
- NVIDIA GeForce RTX 4090 Founders Edition
- NVIDIA GeForce RTX 5070 Ti
- NVIDIA GeForce RTX 5080 Founders Edition
- NVIDIA GeForce RTX 5090 Founders Edition
- NVIDIA GH200 Grace Hopper
- NVIDIA H100
- NVIDIA H200
- NVIDIA HGX B200
- NVIDIA Jetson AGX Thor
- NVIDIA RTX PRO 4500 Blackwell
- NVIDIA RTX PRO 5000 Blackwell
- NVIDIA RTX PRO 6000 Blackwell
- OpenAI GPT-5
- SambaNova SN40L Reconfigurable Dataflow Unit
- Sanctuary AI Phoenix
- Tesla Optimus
- The Stargate Project
- Unitree B2
- Unitree G1
- Unitree H1
0 of 28 fields comparable
⇄ swap sides| Spec | NVIDIA H100 | Alibaba Qwen2.5-72B-Instruct (Q4 quant) |
|---|---|---|
| BF16 TFLOPS (sparse) | 1,979 | — |
| Context Window Tokens K | — | 128 |
| Dual Card Count | — | 2 |
| Dual Card Vram GB | — | 24 |
| Form factor | SXM | — |
| FP16 TFLOPS (dense) | 989.5 | — |
| FP16 TFLOPS (sparse) | 1,979 | — |
| FP32 TFLOPS | 67 | — |
| FP64 Tensor TFLOPS | 67 | — |
| FP64 TFLOPS | 34 | — |
| FP8 TFLOPS (dense) | 1,979 | — |
| FP8 TFLOPS (sparse) | 3,958 | — |
| GPT Version | — | 5 |
| HBM (GB) | 80 | — |
| INT8 TOPS (sparse) | 3,958 | — |
| Memory bandwidth (TB/s) | 3.35 | — |
| Memory type | HBM3 | — |
| NVLink bandwidth (GB/s) | 900 | — |
| Parameter Count B | — | 72 |
| Qwen Version | — | 3 |
| Qwen25 72B Instruct | — | Qwen2.5-72B-Instruct |
| Qwen25 Version | — | 2.5 |
| Qwen3 Largest Dense Checkpoint B | — | 32 |
| RTX 5090 Pairing Vram GB | — | 32 |
| Status Checked | — | 2026-09-24 |
| TDP max (W)↓ better | 700 | — |
| TF32 TFLOPS (sparse) | 989 | — |
| Vram Required GB | — | 44 |