NelsaHost

Hardware AI Models Compatibility Compare

search Login

Can I run Llama 3 8B (q3_k_m) on NVIDIA RTX 3090 Ti?

check_circle

Perfect

Yes, you can run this model!

GPU VRAM

24.0GB

Required

3.2GB

Headroom

+20.8GB

VRAM Usage

0GB 13% used 24.0GB

Performance Estimate

Tokens/sec ~72.0

Batch size 13

Context 8192K

info Technical Analysis

NVIDIA RTX 3090 Ti provides excellent compatibility with Llama 3 8B (8.00B). With 24.0GB of VRAM and only 3.2GB required, you have 20.8GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run Llama 3 8B (8.00B) on NVIDIA RTX 3090 Ti 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 Llama 3 8B (8.00B) on NVIDIA RTX 3090 Ti? expand_more

NVIDIA RTX 3090 Ti has 24.0GB VRAM, which provides 20.8GB of headroom beyond the 3.2GB required by Llama 3 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 8B (8.00B) need? expand_more

Llama 3 8B (8.00B) requires approximately 3.2GB of VRAM.

What performance can I expect? expand_more

Estimated 72 tokens per second.