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Can I run Gemma 2 27B (INT8 (8-bit Integer)) on NVIDIA A100 80GB?

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Perfect

Yes, you can run this model!

GPU VRAM

80.0GB

Required

27.0GB

Headroom

+53.0GB

VRAM Usage

0GB 34% used 80.0GB

Performance Estimate

Tokens/sec ~78.0

Batch size 9

Context 8192K

info Technical Analysis

NVIDIA A100 80GB provides excellent compatibility with Gemma 2 27B (27.00B). With 80.0GB of VRAM and only 27.0GB required, you have 53.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run Gemma 2 27B (27.00B) on NVIDIA A100 80GB without any compromises. Consider using full context length and larger batch sizes for optimal throughput.

tune Recommended Settings

Batch_Size

Context_Length

8192

Inference_Framework

llama.cpp or vLLM

help Frequently Asked Questions

Can I run Gemma 2 27B (27.00B) on NVIDIA A100 80GB? expand_more

NVIDIA A100 80GB has 80.0GB VRAM, which provides 53.0GB of headroom beyond the 27.0GB required by Gemma 2 27B (27.00B). This is plenty of room for comfortable inference with room for KV cache, batching, and extended context lengths.

How much VRAM does Gemma 2 27B (27.00B) need? expand_more

Gemma 2 27B (27.00B) requires approximately 27.0GB of VRAM.

What performance can I expect? expand_more

Estimated 78 tokens per second.