Local AI hardware: DDR4 16GB Computer

Hardware profile
Hardware Memory Bandwidth Computing power vLLM
DDR4 16GB ComputerComputer with 16 GB DDR4-3200 dual-channel RAM 16 GBRAM 51.2 GB/s ~2 TOPS no
Compatible models Estimated speeds, not benchmark results: calculated from memory bandwidth and model size. Real results can differ significantly because there is no precise formula for deriving LLM generation speed from hardware specifications alone.
Model Size Approx. Q4 memory Estimated generation
GPT-OSS 20BMoE 20.9Bactive 3.6B 12.5 GB 9 tok/s4-bit quantization
Instella-MoE 16B ThinkMoE 16Bactive 2.8B 9.6 GB 12 tok/s4-bit quantization
Qwen 3 14BDense 14B 8.4 GB 3 tok/s4-bit quantization
Gemma 3 12BDense 12B 7.2 GB 3 tok/s4-bit quantization
Gemma 4 12BDense 12B 7.2 GB 3 tok/s4-bit quantization
Fara 1.5 9BDense 9B 5.4 GB 5 tok/s4-bit quantization
Ornith 1.0 9BDense 9B 5.4 GB 5 tok/s4-bit quantization
Ornith 1.5 9BDense 9B 5.4 GB 5 tok/s4-bit quantization
Qwen 3.5 9BDense 9B 5.4 GB 5 tok/s4-bit quantization
Qwythos 9BDense 9B 5.4 GB 5 tok/s4-bit quantization
Granite 4.1 8BDense 8B 4.8 GB 5 tok/s4-bit quantization
Granite 4.2 8BDense 8B 4.8 GB 5 tok/s4-bit quantization
Qwen 3 8BDense 8B 4.8 GB 5 tok/s4-bit quantization
Ling 3.0 TinyMoE 7.9Bactive 1.3B 4.7 GB 26 tok/s4-bit quantization
Fara 1.5 4BDense 4B 2.4 GB 11 tok/s4-bit quantization
Gemma 3 4BDense 4B 2.4 GB 11 tok/s4-bit quantization
Qwen 3 4B Instruct 2507Dense 4B 2.4 GB 11 tok/s4-bit quantization
Qwen 3.5 4BDense 4B 2.4 GB 11 tok/s4-bit quantization
Spark X2.5 4BDense 4B 2.4 GB 11 tok/s4-bit quantization
Granite 4.1 3BDense 3B 1.8 GB 15 tok/s4-bit quantization
Granite 4.2 3BDense 3B 1.8 GB 15 tok/s4-bit quantization
Llama 3.2 3B InstructDense 3B 1.8 GB 15 tok/s4-bit quantization
Ministral 3 3BDense 3B 1.8 GB 15 tok/s4-bit quantization
Nanbeige 4.2 3BDense 3B 1.8 GB 15 tok/s4-bit quantization

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