Comparing Efficiency Strategies for LLM Deployment and Summarizing PowerInfer‑2’s Impact
3 Nov 2025
This article situates PowerInfer‑2 among other frameworks that improve LLM efficiency through compression, pruning, and speculative decoding.
Performance Evaluation of PowerInfer‑2: Offloading, Prefill, and In‑Memory Efficiency
3 Nov 2025
PowerInfer‑2 achieves up to 29× speedups over llama.cpp and 13× over LLMFlash by leveraging neuron‑level pipelines and NPU‑centric prefill optimization.
How PowerInfer‑2 Turns Your Smartphone Into an AI Workstation
3 Nov 2025
The cost model leverages SMT‑based solving (Z3) to achieve optimal decoding speed under CPU, I/O, and memory constraints.
How Hybrid AI Models Balance Memory and Efficiency
28 Oct 2025
Mamba and attention are combined in SAMBA to provide effective long-context language modeling with robust performance and exceptional memory recall.
Meet SAMBA: The AI Model That Remembers More and Trains Faster
28 Oct 2025
SAMBA demonstrates how combining recurrence and attention allows for quicker, longer, and more intelligent AI with infinite memory and superior efficiency.
SAMBA Proves Hybrid Design Is the Future of Long-Context Modeling
28 Oct 2025
By combining attention and recurrence, SAMBA reimagines AI efficiency and enables longer, faster, and more intelligent language processing at scale.
Microsoft’s SAMBA Model Redefines Long-Context Learning for AI
28 Oct 2025
SAMBA combines attention and Mamba for linear-time modeling and context recall for millions of tokens.
Researchers Just Built a Plug-and-Play Brain for LLMs
22 Oct 2025
With a plug-and-play value model, Q★ improves LLM reasoning and achieves cutting-edge coding and math correctness without the need for fine-tuning.
Teaching LLMs How to “Think Twice”
22 Oct 2025
Q* merges A* search with LLMs to boost multi-step reasoning, reduce hallucinations, and enable smarter AI deliberation.