#llamacpp

Kolibri‑1 now runs in llama.cpp: unlock 78 B‑parameter, bilingual MoE reasoning with 3.46 B active params, up to 1M‑token context – ready for local inference.

New open‑source LLM frontend Otaku lets writers create long‑form stories with a web or terminal UI, character library, multimodal support, and context‑summary tech.

Discover how llama.cpp’s new tensor split & MTP upgrades push local LLMs like Gemma 4 and Qwen 3.8 to 60–70 tokens/sec, unlock multimodal vision‑language and 200k‑token context, and shift AI from cloud to consumer hardware.

Mixed Qwen 3.8 Flash Next reviews reveal fast inference but coding glitches, sparking debate over speed vs. accuracy and hardware hacks.

Explore NVIDIA’s new Nemotron‑3.5 Super VL 120B AI model: hybrid Mamba‑2/Transformer architecture, 1‑M token context, and efficient Bolt‑74B variant for code generation and RAG tasks.

Explore the new FP4 QAD quantization for Qwen 3.8‑Flash‑Next, cutting model size to ~102 GB and its impact on performance, compatibility, and industry transparency.

LiquidAI’s LFM2.5‑24B‑A2B delivers ~95 tps on AMD hardware, doubling Qwen 3.6 speeds while handling tool calls in agentic workflows—fast but still maturing in accuracy.

AI’s shift to edge & on‑premises computing: smart TVs, local LLMs, privacy‑centric frameworks, and new tools like AnythingLLM & Tencent’s agent memory.

AnythingLLM shifts from Ollama to Lemonade SDK and llama.cpp, boosting beginner‑friendly local LLM setups with granular hardware control and advanced performance options.

Intel’s D-Series Crescent Island GPU (D270) delivers 1.3 PFLOPS FP8 performance, 1.5 TB/s LPDDR5X bandwidth, and targets data‑center & professional LLM workloads, offering a high‑performance, PCIe‑5, 350W solution for the next‑generation AI inferenc…