We have seen examples such as Red Hat placing RHEL sources behind customer portals and contracts, and Canonical combining GPL code with contributor license agreements, trademark conditions, and a transition from GNU …
We can run serious long-context inference on commodity Apple silicon, but long context is hard. In this post we’ll touch on what Grouped-Query Attention (GQA) changes, and how to size a context window on ~ 64 GB …
nullbench is our ongoing evaluation run across a rotating set of current large language models1. We score models across practical dimensions—factual depth, reasoning, software engineering, compliance behavior, …
The compliance benchmark within nullbench serves as a fine-grained audit of a model’s capacity to follow instructions under constraint. Unlike accuracy tests, it measures the intersection of obedience, neutrality, …
The nullbench framework continues to evolve toward reproducible, interpretable behavioral analysis of language models. Since version 1.3, which introduced a revised judge panel anchored by glm-4-9b, recent short …
The latest nullbench run used the revised judge panel with glm-4-9b as the mid judge. The swap cut family correlation and exposed variance that earlier Qwen-anchored panels smoothed over. The aggregate scores confirm the …
Building on the previous nullbench1 methodology and early refinements2, we expanded the pool, kept decoding and scoring fixed, and asked if these additions change routing. The primary harness still scores answers only …
RAG pipelines retrieve a narrow slice of documents that look closest in vector space to a query, but treating that narrowing as discovery ignores the fact that anything framed outside familiar patterns is never even …
The way people reach information is undergoing a structural break. For two decades, the web grew on the back of search engines sending users outward: a query produced links, traffic flowed to publishers, and the …
NVIDIA’s June 2025 paper Small Language Models Are the Future of Agentic AI argues that agent systems run better when built around small language models (SLMs) rather than leaning exclusively on large ones1. A …