#llamacpp

Alibaba unveils Qwen 4, a 5‑to‑10 trillion‑parameter AI model, plus a new AI chip at Apsara Conference—setting a new scale for generative AI.

Discover how “JEV” turns LLMs into lightning‑fast single‑token classifiers—cut latency, slash costs, and unlock instant confidence scores for real‑world tasks.

Discover how the new llamAmpere fork boosts LLM inference on NVIDIA Ampere GPUs, delivering 90+ TPS and 240k‑token context on RTX 3090—unleash local AI power today.

Explore Voodoo Dynamic Quant, an open‑source tool that outperforms static methods at low‑bit levels, offering per‑tensor optimization for smaller AI models.

New llama.cpp PR adds CPU support for DeepGrove’s Maple 20B‑A1B ternary MoE model—boosting local LLM performance on Macs, iPhones, and future GPU acceleration.

Swift‑Qwen3.8‑27B cuts token loops by 58% and speeds up 1.95× while keeping near‑perfect accuracy—ideal for fast, accurate LLM use on modest hardware.

Optimize local LLMs without cloud reliance: see how llama.cpp and halogen‑flash‑server double decoding speed and boost prefill on consumer hardware.

New llama.cpp Flash Attention tweak boosts AMD GPU performance on RDNA4 (R9700, RX 9060 XT) for long‑context AI tasks.

Discover OUI‑1, OpenUI’s fine‑tuned model for fast OpenUI‑Lang UI generation—weights on Hugging Face, new licensing, and local deployment tips.

Explore the new CyberTiel 35B‑A3B model—4‑bit quantized, uncensored, and faster than Qwen 3.8‑27B. See how it outperforms Opus 4.6 on real coding tasks and what that means for secure software engineering.