I've been using the 27B series for a while now. It's so good, I don't even use a custom chat template and barely ever saw tool call failures. My latest model & engine of choice were ukisai/Swift-1.5-Qwen3.8-27b-NVFP4 running on NInfer. Recently I began experimenting with QFN, more specifically ukisai/Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-GGUF:IQ3_S running on Basalt. The model seems pretty good, but I see quite a lot of tool call failures. Sometimes I see the model chaining up to four or five failed tool calls until it finally gets it right. Using the exact same harness & setup for both (OpenCode). Tool calls could be file edits, playwright commands, or anything really. I'm unsure if this is a quantization issue (IQ3_S), a model issue (QFN), or an engine issue (Basalt). Has anyone experienced tool calling issues with QFN? Because it sure was not an issue with Q3.8-27B on any quant (4bpw+) and engine (llama.cpp, vLLM, exllamav3, NInfer) I tried. I'm planning some runs of BFCL v3 or v4 with different configurations to see if I can collect better data on tool calling. I'd appreciate if anyone would share their findings on tool calling success rates with QFN, and if there is anything that can be done to improve it.   submitted by   /u/Tormeister [link]   [comments]