NVIDIA RTX 5060 Ti

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4d
Local GPU server benchmarks 12 models from 4B to 35B parameters
A Reddit developer says they built a Linux server with two RTX 5060 Ti cards providing 32 GB of total VRAM, running vLLM in Docker. The developer reports testing 12 models from 4B to 35B parameters on complete datasets including IFEval, IFBench, ARC AGI 1, SimpleQA, SimpleQA Verified and SciCode, both with thinking enabled and disabled. The system also records wall-clock duration and token throughput to produce a time-efficiency score, although the methodology and results are self-reported.
r/LocalLLaMA · 🔥 0
5d
llama.cpp Tensor Splitting Shows Promise Over PCIe 3.0 x1
A community test running Gemma 4 31B Q5 on two RTX 3060 12GB GPUs reported that switching llama.cpp from layer splitting to tensor splitting raised throughput from 14 to 20 tokens per second, a 42% increase, with the second GPU connected through PCIe 3.0 x1. The author said the exact home configuration was not extensively tested while awaiting a PSU upgrade. A separate test on two RTX 5060 Ti 16GB GPUs with PCIe Gen 3 x8 links recorded 20.7 tokens per second for tensor splitting versus 11.7 for layer splitting during prompt generation, while decoding showed transfer rates of roughly 90–110 MB/s in each direction. The author cautioned that the results do not prove PCIe 3.0 x1 has no performance penalty and that average throughput does not capture latency, synchronization overhead, or short-transfer bursts.
r/LocalLLaMA · 🔥 0

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