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Can I run Qwen 2.5 14B (INT8 (8-bit Integer)) on NVIDIA RTX 3090 Ti?

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Perfect
Yes, you can run this model!
GPU VRAM
24.0GB
Required
14.0GB
Headroom
+10.0GB

VRAM Usage

0GB 58% used 24.0GB

Performance Estimate

Tokens/sec ~60.0
Batch size 3
Context 131072K

info Technical Analysis

NVIDIA RTX 3090 Ti provides excellent compatibility with Qwen 2.5 14B (14.00B). With 24.0GB of VRAM and only 14.0GB required, you have 10.0GB of headroom for comfortable inference. This allows for extended context lengths, batch processing, and smooth operation.

lightbulb Recommendation

You can run Qwen 2.5 14B (14.00B) 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
3
Context_Length
131072
Inference_Framework
llama.cpp or vLLM

help Frequently Asked Questions

Can I run Qwen 2.5 14B (14.00B) on NVIDIA RTX 3090 Ti? expand_more
NVIDIA RTX 3090 Ti has 24.0GB VRAM, which provides 10.0GB of headroom beyond the 14.0GB required by Qwen 2.5 14B (14.00B). This is plenty of room for comfortable inference with room for KV cache, batching, and extended context lengths.
How much VRAM does Qwen 2.5 14B (14.00B) need? expand_more
Qwen 2.5 14B (14.00B) requires approximately 14.0GB of VRAM.
What performance can I expect? expand_more
Estimated 60 tokens per second.

GPU

memory
NVIDIA RTX 3090 Ti
24.0GB VRAM

AI Model

smart_toy
Qwen 2.5 14B (14.00B)
14.00B params

Alternative Quantizations

q3_k_m Perfect Q4_K_M (GGUF 4-bit) Perfect

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