Fast and Hard Code

chad/whichlang

What programming language do LLMs default to when you don't tell them? A small benchmark.

distil labs — Replace LLMs with Custom Small Language Models

Train and deploy custom small language models that are faster, cheaper, and just as accurate as LLMs.

Mitigating Cross-Lingual Cultural Inconsistencies in LLMs via...

Despite their impressive capabilities, multilingual large language models (MLLMs) frequently exhibit inconsistent behaviour when the prompt's language changes. While such adaptation is generally...

Wolfram LLM Benchmarking Project

Results from Wolfram's ongoing tracking of LLM performance. The benchmark is based on a Wolfram Language code generation task.

Best LLM for Coding 2026 | AI Coding Model Rankings & Benchmarks

Which AI model writes the best code? We rank every major LLM — open and closed source — across SWE-bench, HumanEval, LiveCodeBench, and Terminal-Bench coding benchmarks. Compare the best LLMs for coding, software engineering, and programming.

The Return of Language-Oriented Programming | Middle of Nowhere

I’ve been wondering what LLMs mean for language design and implementation. Some believe that, because language models are obviously trained on existing content, they are inherently less capable of assisting users with new programming languages. Intuitively this makes sense. However:

The Case Against LLMs as Rerankers

Authors: Apoorva Joshi, Zhenmei Shi, Akshay Goindani, Hong LiuResearch Leads: Zhenmei Shi, Akshay Goindani, Hong Liu Large language models are increasingly being used for a broad range of tasks, in…

Beyond Standard LLMs

Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers

Translating non-trivial codebases with Claude

I don’t think it’s [me writing about LLMs] likely to happen anytime soon: I prefer to write about things that I’m excited about.

Aider LLM Leaderboards

Quantitative benchmarks of LLM code editing skill.

MCP servers vs. skills: Choosing the right context for your AI | Red Hat Developer

Large language models (LLMs) are efficient general-purpose tools, but they work much better when you give them the right context

Magicoder: Empowering Code Generation with OSS-Instruct

We introduce Magicoder, a series of fully open-source (code, weights, and data) Large Language Models (LLMs) for code that significantly closes the gap with top code models while having no more...

Writing Code Is Easy. Reading It Isn’t.

Writing code is easy. Once you have a solution in mind, and have mastered the syntax of your favorite programming language, writing code is easy. Having an LLM write entire functions for you? Even eas

Large language model

A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots.[1] Biased or inaccurate training data can make an LLM's output less reliable.[2]

Why Can’t Powerful LLMs Learn Multiplication?

These days, large language models (LLMs) can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to 4-digit multiplication, a task taught in elementary school, even state-of-the-art systems fail. Why? A new paper by Computer Science PhD student Xiaoyan Bai and Faculty Co-Director of the Data Science Institute’s …