Qwen3.8 27B

User benchmarks eight models on 33 DevOps agent tasks with taracode 3.3.1 on taraengine 0.3.1, at temperature 0 and 32k context, one run per model. On an RTX 5090 (32 GB), qwen3.8:27b leads at 97% pass rate and 126 tok/s, using 23.2 GiB of VRAM. Setup is taraengine with Q4_K_M weights and MTP speculative decoding, which the engine pairs with seven of the eight models. The same catalog on an M4 Max (48 GB) runs 3.0 to 4.4 times slower, with qwen3.8:27b at 39 tok/s and 94% pass rate. Against an earlier Ollama 0.35 board on the same 5090, gemma4:31b rose from 64 to 164 tok/s, gemma4:12b from 138 to 308 and qwen3.6:35b from 226 to 388, with every pass rate within four tasks. The user notes one run per row, rows within four tasks are a tie, and 33 tasks is small.