RTX 5060 Ti 16GB Local LLM Findings: 30B Still Wins, 35B UD Is Surprisingly Fast

Imaginary-Anywhere23

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r/LocalLLaMA

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RTX 5060 Ti 16GB Local LLM Findings: 30B Still Wins, 35B UD Is Surprisingly Fast.

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Bought 5060ti 16gb and tried various model.

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This is the short version for me deciding what to run on this card with `llama.cpp`, not a giant benchmark dump.

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Machine: * RTX 5060 Ti 16 GB * DDR4 now at 32 GB * llama-server `b8373` (`46dba9fce`) Relevant launch settings: * fast path: `fa=on`, `ngl=auto`, `threads=8` * KV: `-ctk q8_0 -ctv q8_0` * 30B coder path: `jinja`, `reasoning-budget 0`, `reasoning-format none` * 35B UD path: `c=262144`, `n-cpu-moe=8` * 35B `Q4_K_M` stable tune: `-ngl 26 -c 131072 --fit on --fit-ctx 131072 --fit-target 512M` Short version: * Best default coding model: `Unsloth Qwen3-Coder-30B UD-Q3_K_XL` * Best higher-context coding option: the same `Unsloth 30B` model at `96k` * Best fast 35B coding option: `Unsloth Qwen3.5-35B UD-Q2_K_XL` * `Unsloth Qwen3.5-35B Q4_K_M` is interesting, but still not the right default on this card What surprised me most is that the practical winners here were not just "smaller is...

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