#BenchMarkS

Most of the benchmarks are in English. But a large portion of the world's population doesn't speak English (around 80 %). We can see from SWE Pro or the stagnation at DeepSWE that we're kind of measuring in a vacuum right now.…

Moritz Hardt, author of a new book on benchmarks, believes these “standardized tests” for artificial intelligence are fundamentally broken — but not unfixable.

In this article, you will learn what the major AI agent benchmarks measure, how they differ from traditional model benchmarks, and how to use them as directional signals rather than performance guarantees.

Quick Introduction We have all been on forums, chats, reddit, discord, youtube, or somewhere and heard “Oh! Model XYZ is AMAZEBALLZ!zomgwtfbbq” then downloaded it (or more likely, some quantized form of it) and said “eww… This sucks!” This post is going…

Ox Alpha is a reasoning model designed for coding, sustained agentic work, and production workloads. This model is free to use. 1,048,576 token context window, maximum output of 131,072 tokens.

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series. $2.50 per million input tokens, $15 per million output tokens. 1,050,000 token context window, maximum output of 128,000 tokens. Higher uptime with 3 providers.…

I've been using AI fairly heavily since last November and the whole thing is a funny experience. An agent will do something that, if a human did it, you'd immediately fire them.…

It's running very close to AMD's EPYC, which is incredible for a first-generation custom server core from NVIDIA.

Why Evals Matter Training a model is only half the job. Without a systematic way to...

Running modern AI models locally on older hardware sounds almost impossible. But with smaller models...

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is...

Evaluate LLM models systematically using benchmarks, human evaluation, LLM-as-judge frameworks, and production A/B testing.

A complete walkthrough of Interfaze: what it is, who we benchmark against (Gemini-3-Flash, Claude-Sonnet-4.6, GPT-5.4-Mini, Grok-4.3, plus task specialists like Reducto, SAM 3, Scribe v2), full results across 9 benchmarks, and code examples for OCR,…

A no-training graph heuristic beats generative recommenders on 10 of 14 benchmarks, exposing shortcut-solvable datasets. Relative NDCG@10 gains hit 44

list vs tuple vs set: What I Found After 100K Iterations I ran 100,000 read/write...

From Dev.to - cloud: Cloud Provisioning Benchmarks: AWS vs Azure vs GCP — 2026-05-07

From Dev.to - terraform: Benchmark scaling in Istio 1.20 vs Terraform 1.7: What You Need to Know

Multimodal LLMs show 10-20 point accuracy drops from benchmarks to real hospital cases. GPT-4.1 falls from 42.25% to 24.65%.