A Reddit post in r/LocalLLaMA introduces a GGUF release of Qwen3.5-122B-A10B Uncensored (Aggressive) alongside new K_P quants. The author claims 0/465 refusals and zero capability loss, but those results are presented as the author’s own tests rather than independent verification.
Hacker News pushed Microsoft's bitnet.cpp back into view, treating it less as a new 100B checkpoint and more as an infrastructure play for 1.58-bit inference and lower-power local LLM deployment.
A LocalLLaMA thread highlighted ongoing work to add NVFP4 quantization support to llama.cpp GGUF, pointing to potential memory savings and higher throughput for compatible GPU setups.
A high-scoring LocalLLaMA post benchmarked Qwen3.5-27B Q4 GGUF variants against BF16, separating “closest-to-baseline” choices from “best efficiency” picks for constrained VRAM setups.
A high-engagement r/LocalLLaMA thread reviewed Unsloth’s updated Qwen3.5-35B-A3B dynamic quantization release, including KLD/PPL data, tensor-level tradeoffs, and reproducibility artifacts.
A high-engagement LocalLLaMA follow-up benchmark reports that Qwen3.5-35B-A3B runs best on the tested RTX 5080 setup with Q4_K_M quantization, KV q8_0, and --fit without explicit batch flags.
A popular LocalLLaMA post highlights draft PR #19726, where a contributor proposes porting IQ*_K quantization work from ik_llama.cpp into mainline llama.cpp with initial CPU backend support and early KLD checks.
A high-engagement LocalLLaMA post highlighted local deployment paths for MiniMax-M2.5, pointing to Unsloth GGUF packaging and renewed discussion on memory, cost, and agentic workloads.
A r/MachineLearning discussion reported that one INT8 ONNX model produced large on-device accuracy variance across five Snapdragon chipsets, from 91.8% down to 71.2%, despite identical weights and export settings.
A popular r/LocalLLaMA post details Heretic 1.2 with PEFT/LoRA updates, optional 4-bit processing, MPOA support, VL coverage, and automatic resume features for long local optimization runs.