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Qwen 2 5 32b

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Data graphic: Llama 3.3-70B needs 131.5 GB for its FP16/BF16 weights, which takes two 80GB H100s TP=2 unquantized, while Qwen 2.5-32B needs 60.5 GB and runs native BF16 on one H100; bars compare them with Gemma 2 27B 50.7 GB and Mistral Small 3 44.7 GB against 24GB and 80GB GPU lines. A benchmark table shows Qwen ahead on MATH 83.1% vs 77.0% and LiveCodeBench 51.2% vs 43.5% , and Llama ahead on IFEval 92.1% vs 79.5% and MMLU 86.0% vs 83.3% .

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Qwen 2.5-32B vs. Llama 3.3-70B: Enterprise Foundation Model Sizing, Benchmarks, and Local VRAM Economics

Compare Qwen 2.5-32B vs. Llama 3.3-70B on benchmarks, GPU VRAM sizing, and costs. Discover the best open-weight LLM architecture for enterprise AI deployments.

Aug 15 · 8 min