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Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.
NVIDIA RTX 5060 8GB · llama.cpp · 8,192 ctx
User reports Qwen3.8-27B at 30.10 tok/s median decode on an RTX 5060 8GB, over five runs at an occupied 8192-token prompt. Setup is llama.cpp with UD-IQ2_XXS weights and q4_0 KV cache, 65/65 layers on CUDA, peak VRAM 7767 MiB. A short-context FULL_GPU decode of 31.39 tok/s and a ctx512 control of 18.11 tok/s are also given; quality gate and uncensored checkpoint are not done.
NVIDIA RTX 5060 8GB · llama.cpp
User asks whether speculative decoding (MTP) is still worth enabling for a 35B A3B MoE model offloaded across an 8GB RTX 5060 and 32GB of system RAM. Current llama-server setup uses a Q4_K_XL GGUF with a Q8 KV cache, flash attention on, 4096 batch and ubatch, 16 CPU cores, 40 MoE layers on CPU and 99 GPU layers, yielding about 40 t/s generation and 500 t/s prompt processing without MTP. User recalls earlier reports that MTP hurt prompt processing and wants to know if that is still the case and how others configure llama-server.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking