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Can I run Llama 3.1 8B on NVIDIA H100 PCIe?

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Perfect

Yes, you can run this model!

GPU VRAM

80.0GB

Required

16.0GB

Headroom

+64.0GB

VRAM Usage

0GB 20% used 80.0GB

Performance Estimate

Tokens/sec ~93.0

Batch size 32

Context 128000K

info Technical Analysis

NVIDIA H100 PCIe provides excellent compatibility with Llama 3.1 8B (8.00B). With 80.0GB of VRAM and only 16.0GB required, you have 64.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run Llama 3.1 8B (8.00B) on NVIDIA H100 PCIe without any compromises. Consider using full context length and larger batch sizes for optimal throughput.

tune Recommended Settings

Batch_Size

Context_Length

128000

Inference_Framework

llama.cpp or vLLM

help Frequently Asked Questions

Can I run Llama 3.1 8B (8.00B) on NVIDIA H100 PCIe? expand_more

NVIDIA H100 PCIe has 80.0GB VRAM, which provides 64.0GB of headroom beyond the 16.0GB required by Llama 3.1 8B (8.00B). This is plenty of room for comfortable inference with room for KV cache, batching, and extended context lengths.

How much VRAM does Llama 3.1 8B (8.00B) need? expand_more

Llama 3.1 8B (8.00B) requires approximately 16.0GB of VRAM.

What performance can I expect? expand_more

Estimated 93 tokens per second.