“Newelle, AI assistant for Linux, has been updated to 1.2!”

“The goal was to evaluate whether large language models can determine causal and logical consistency between a proposed character backstory and an entire novel (~100k words), rather than relying on local plausibility.”

“Databricks 基盤モデルAPIは多種多様なLLM APIを提供しており、Llamaのようなオープンウェイトモデルもあれば、GPT-5.2やClaude Sonnetなどのプロプライエタリモデルをネイティブ提供しています。”

“Llama-3.2-1B-4bit → 464 tok/s”

“The article highlights discussions on X (formerly Twitter) about which small LLM is best for Japanese and how to disable 'thinking mode'.”

“The Raspberry Pi AI HAT+ 2 includes a 40TOPS AI processing chip and 8GB of memory, enabling local execution of AI models like Llama3.2.”

“This article dives into the implementation of modern Transformer architectures, going beyond the original Transformer (2017) to explore techniques used in state-of-the-art models.”

“Once connected, the Raspberry Pi 5 will use the AI HAT+ 2 to handle AI-related workloads while leaving the main board's Arm CPU available to complete other tasks.”

“OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education.”

“The key is (1) 1B-class GGUF, (2) quantization (Q4 focused), (3) not increasing the KV cache too much, and configuring llama.cpp (=llama-server) tightly.”

“"This article provides a valuable benchmark of SLMs for the Japanese language, a key consideration for developers building Japanese language applications or deploying LLMs locally."”

“Overall, the findings demonstrate that carefully designed prompt-based strategies provide an effective and resource-efficient pathway to improving open-domain dialogue quality in SLMs.”

“前回の記事ではAMD Ryzen AI Max+ 395でgpt-oss-20bをllama.cppとvLLMで推論させたときの性能と精度を評価した。”

“This is an abliterated version of the allegedly leaked Llama 3.3 8B 128k model that tries to minimize intelligence loss while optimizing for compliance.”

“Unable to extract a direct quote from the provided context. The title suggests claims of 'fabrication' and criticism of leadership.”

“The model struggled to write unit tests for a simple function called interval2short() that just formats a time interval as a short, approximate string... It really struggled to identify that the output is "2h 0m" instead of "2h." ... It then went on a multi-thousand-token thinking bender before deciding that it was very important to document that interval2short() always returns two components.”

“due to being a hybrid transformer+mamba model, it stays fast as context fills”

“The core issue was that when two conflicting documents had the exact same reliability score, the model would often hallucinate a 'winner' or make up math just to provide a verdict.”

“The initial conclusion was that Llama 3.2 Vision (11B) was impractical on a 16GB Mac mini due to swapping. The article then pivots to testing lighter text-based models (2B-3B) before proceeding with image analysis.”

“The author, a former network engineer, is new to Mac and IT, and is building the environment for app development.”

“"Suffices for llama?"”

“The main findings is that when running certain models partially offloaded to GPU, some models perform much better on Vulkan than CUDA”

“By varying epsilon on this one dim: Negative ε: outputs become restrained, procedural, and instruction-faithful Positive ε: outputs become more verbose, narrative, and speculative”

“Automatically scrapes documentation websites and converts them into organized, categorized reference files with extracted code examples.”

“Is there anything ~100B and a bit under that performs well?”

“Which one of these works the best in production: 1. bge m3 2. embeddinggemma-300m 3. qwen3-embedding-0.6b”

“XiaomiMiMo/MiMo-V2-Flash has 310B param and top benches. Seems to compete well with KimiK2Thinking, GLM4.7, MinimaxM2.1, Deepseek3.2”

“Tool calling wise **gpt-oss** is leagues ahead of all the others, at least in my experience using them”

“Instruction-following capabilities improve substantially (+46% to +75% in IFEval for Llama-3.2-1B and 3B models).”

“(No specific quote available from the provided context)”

“It's incredibly fast at generating tokens compared to other models (certainly faster than both GLM and Minimax).”

“In the AI boom, chatbots and GPTs come and go quickly.”

“Modern language models preserve the geometric substrate that enables Bayesian inference in wind tunnels, and organize their approximate Bayesian updates along this substrate.”

“Looking for anyone who has some benchmarks they would like to share. I am trying to optimize my EVO-X2 (Strix Halo) 128GB box using GLM-4.5-Air for use with Cline.”

“What are 7b, 20b, 30B parameter models actually FOR?”

“Is 96GB too expensive? And AI community has no interest for 48GB?”

“How many of you used --fit flag on your llama.cpp commands? Please share your stats on this(Would be nice to see before & after results).”

“I’m seeing all these charts claiming GLM 4.7 is officially the “Sonnet 4.5 and GPT-5.2 killer” for coding and math.”

“"It is #1 overall amongst all open weight models and ranks just behind Gemini 3 Pro Preview, a 15-place jump from GLM 4.6"”

“Pruning $8$--$16$ attention sublayers yields up to $1.30\times$ higher inference throughput while keeping average zero-shot accuracy within $2\%$ of the unpruned baseline.”

“gpt-oss-20bをCPUで推論したらGPUより爆速でした。”

“The summary indicates a focus on post-transformer inference techniques, suggesting the compression and accuracy improvements are achieved through methods applied after the core transformer architecture. Further details from the original source would be needed to understand the specific techniques employed.”

“”

“The article likely details the specific techniques used to adapt LLaMA for these tasks, including any modifications to the model architecture or training procedures. It would be interesting to see the performance metrics of Llamazip compared to other compression methods and dataset detection techniques.”

“Meta's Llama 3.1 can recall 42 percent of the first Harry Potter book”

“Cerebras achieves 2,500T/s on Llama 4 Maverick (400B)”

“”

“Achieved 4.2x Sonnet 3.5 accuracy for code generation.”

“Llama.cpp now supports Qwen2-VL (Vision Language Model)”

“The author spent a lot of time and money on this project and considers themselves the target audience for Hacker News.”