Everything I'd send you, in one place

Epoch Capabilities Index

Epoch AI's index combining many benchmarks into a single capability scale for comparing AI models over time, with a release-date graph view.

Arena AI

A public leaderboard where visitors chat with, compare and vote on AI models, producing community rankings for language, image and code models based on real-world use.

2026 in LLMs (So Far) — Simon Willison

Simon Willison's annotated slides and notes from his closing keynote at WeAreDevelopers World Congress North America (Sept. 2026): a chronological tour of the year's LLM developments, starting with the November 2025 models that made coding agents start working.

Upstage Releases Solar Mini 4 (Artificial Analysis)

Artificial Analysis on Solar Mini 4, a proprietary reasoning model from Korean lab Upstage. It scores 24 on the Artificial Analysis Intelligence Index, with Upstage reporting 35B total and 3B active parameters, and is priced at $0.10/$0.40 per million input/output tokens — though it costs about 5x as much per task as GPT-6 Luna (max).

Claude Sonnet 5.5 Reaches #2 on the Artificial Analysis Intelligence Index

Artificial Analysis benchmark write-up of Anthropic's Claude Sonnet 5.5: scores 56 on the Intelligence Index, two points behind Opus 5.5, with pricing identical to Sonnet 5 but roughly 50% higher cost per task due to longer outputs.

Introducing Claude Opus 5.5 (Anthropic)

Anthropic's own announcement of Claude Opus 5.5, published 22 September 2026 — the first model in the Claude 5.5 family. The company's claims, in its own words: it performs at the level of Claude Fable 5.1 on most work and costs 40% less to run than Opus 5 on typical workloads; on Anthropic's automated behavioural audit, its most comprehensive internal alignment test, it scores the highest of any model the company has tested. The page also cites early-tester anecdotes, including one completing a 680,000-line code migration in under a day, and a result of succeeding 39 times out of 40 on a page-load optimisation task. It is Anthropic's first release since the company publicly called for pacing the frontier, and it was tested before release by external evaluators including METR and Frontier Design.

Why I recommend it: Read this as a primary source, not as a review. Every performance and cost figure on the page was produced by the company selling the model, on tests it designed — that does not make them false, it makes them unchecked by anyone with a reason to doubt them. The checkable part is the external pre-release testing by METR and Frontier Design, so that is the part to weigh. Note too that '40% less to run than Opus 5' compares Anthropic with its own older model and says nothing about a rival's price, and that the standout numbers come from hand-picked early testers rather than a measured success rate you can plan around. The announcement is free to read; using the model itself is not free beyond whatever the current Claude free tier allows.

DeepSeek

DeepSeek's chat assistant. Free tier gives unlimited messages and file uploads on a daily-reset quota; no payment required. One of the most significant free AI releases of the past two years.

Why I recommend it: Worth trying on reasoning-heavy work and long documents. Note it is a Chinese service — read its data terms before pasting anything confidential.

Epoch AI Benchmarking Hub

Research-grade tracking of what AI models can do and how that has changed over time, with the data and methods published. Free.

From the site: Our hub for benchmark results, featuring the performance of leading AI models on challenging tasks. It includes results from benchmarks administered internally by Epoch AI as well as data collected from external sources. Explore trends in AI capabilities across time, by benchmark, or by model.

Why I recommend it: For the longer view rather than this week's launch — they show their working, which most leaderboards do not.

Artificial Analysis

Independent benchmarking of the major AI models on speed, price and quality, with the numbers side by side. Free to read.

From the site: Comparison and analysis of AI models and API hosting providers. Independent benchmarks across key performance metrics including quality, price, output speed & latency.

Why I recommend it: Where I check what a model actually costs per million words before believing a "cheap" claim.

LMArena

Head-to-head model comparisons voted on by the public: you see two anonymous answers to the same prompt and pick the better one, and the rankings come from those votes. Free.

From the site: Chat, compare, vote for the world's best AI models. Join the community shaping the public leaderboard for LLMs, image, and code models through real-world evaluation.

Why I recommend it: The closest thing to a fair fight between models on ordinary prompts, instead of marketing claims. Votes are taste as much as accuracy, so read it as popularity with a purpose.