v0.7.0
LLM inference in C/C++. Contribute to ggml-org/llama.cpp development by creating an account on GitHub.
llama.cpp11 min read
Ahead of AI (Raschka)
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Agents on live hardware: reason where you must, engineer everywhere else
CoreWeave Blog10 min read
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llama.cpp1 min read
Language Models for Text Classification: From Bag-of-Words to Jev
A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency
Ahead of AI (Raschka)33 min read
LLM Research Papers: The 2026 List (January to May)
A curated roundup of notable LLM research papers that came out this year
Ahead of AI (Raschka)6 min read
Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention
From Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs
Ahead of AI (Raschka)22 min read
My Workflow for Understanding LLM Architectures
A learning-oriented workflow for understanding new open-weight model releases
Ahead of AI (Raschka)1 min read
Components of A Coding Agent
How coding agents use tools, memory, and repo context to make LLMs work better in practice
Ahead of AI (Raschka)14 min read
A Visual Guide to Attention Variants in Modern LLMs
From MHA and GQA to MLA, sparse attention, and hybrid architectures
Ahead of AI (Raschka)18 min read
A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026
A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026
Ahead of AI (Raschka)21 min read
Categories of Inference-Time Scaling for Improved LLM Reasoning
Inference scaling has become one of the most effective ways to improve answer quality and accuracy in deployed LLMs.
Ahead of AI (Raschka)3 min read
The State Of LLMs 2025: Progress, Problems, and Predictions
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.
Ahead of AI (Raschka)28 min read
LLM Research Papers: The 2025 List (July to December)
In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.
Ahead of AI (Raschka)2 min read
From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates
Understanding How DeepSeek's Flagship Open-Weight Models Evolved
Ahead of AI (Raschka)24 min read
Beyond Standard LLMs
Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers
Ahead of AI (Raschka)30 min read
Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)
Multiple-Choice Benchmarks, Verifiers, Leaderboards, and LLM Judges with Code Examples
Ahead of AI (Raschka)27 min read
Understanding and Implementing Qwen3 From Scratch
Previously, I compared the most notable open-weight architectures of 2025 in The Big LLM Architecture Comparison. Then, I zoomed in and discussed the various architecture components in From GPT-2 to gpt-oss: Analyzing the Architectural Advances on a conceptual level.
Ahead of AI (Raschka)2 min read
From GPT-2 to gpt-oss: Analyzing the Architectural Advances
OpenAI just released their new open-weight LLMs this week: gpt-oss-120b and gpt-oss-20b, their first open-weight models since GPT-2 in 2019. And yes, thanks to some clever optimizations, they can run locally (but more about this later).
Ahead of AI (Raschka)23 min read
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