According to recent news, NVIDIA’s Blackwell GPUs are exceptionally powerful, as widely recognized. But just how powerful are they?
Beyond official promotional data, we now have the first set of actual test results from MLCommons MLPerf v4.1, the top platform for evaluating AI training and inference performance.
The comparison is between two generations of servers: HGX B200 and HGX H200. The former features up to eight Blackwell B200 GPUs, each with a power consumption of up to 1000W.
In the GPT-3 pre-training task, Blackwell’s performance doubled compared to the previous Hopper generation.
In the fine-tuning task for Llama 2 with 70 billion parameters, Blackwell’s performance saw an even more impressive 2.2x improvement.
Notably, the Blackwell platform integrates ConnectX-7 SuperNICs, Quantum-2 InfiniBand switches, and fifth-generation NVLink interconnects, ensuring optimal communication between nodes. This enables balanced distribution of AI training workloads, significantly boosting overall efficiency.
For instance, with the same GPT-3 175 billion parameter performance, Hopper requires up to 256 GPUs, whereas Blackwell needs only 64.
Source: MLCommons MLPerf
Related:
- NVIDIA B200: Power Specs And More Details Revealed!
- The Secrets Behind DeepSeek R1 Training Revealed
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