Qwen2.5 7B Coder

User benchmarks llama.cpp, LM Studio, and Ollama on an RTX 5060 Ti 16GB and an Apple M3 Max 36GB, serving Qwen2.5-Coder-7B Q4 GGUF. On the RTX 5060 Ti, llama.cpp reaches 77.0 tok/s, LM Studio 76.8 tok/s (0.3% behind), and Ollama 69.1 tok/s (10.3% slower). On the M3 Max, llama.cpp reaches 53.5 tok/s, Ollama 46.2 tok/s (14% slower), and LM Studio 38.2 tok/s (29% slower). The metric is wall-clock tokens per second over a 12-prompt suite with 256 tokens generated per prompt and greedy decoding. The author attributes the gap to wrapper overhead rather than the shared llama.cpp engine.