Meta's marketing for Llama 4 Scout leads with a seductive number: 17 billion active parameters.
754 billion parameters. 40 billion active.
DeepSeek dropped V4 Pro and V4 Flash on Wednesday, and the numbers shut up most of the skeptics before they could finish typing. V4 Pro — 1.
Twenty-four hours. That's how long GPT-5.
Google DeepMind released Gemma 4 at the start of April, and the AI community immediately zeroed in on the benchmark charts.
Two weeks ago, Z.ai (the company formerly known as Zhipu AI) dropped an open-weight model that claims to beat Claude Opus 4.
Qwen's latest coding model has 80 billion parameters and uses 3 billion of them.
Llama 4 Scout hit 1.2 million downloads in its first two weeks on HuggingFace.
The most important thing Google shipped with Gemma 4 isn't a model. It's a license.
A Chinese AI lab just shipped the world's best coding model — 744 billion parameters, MIT license, trained entirely on Huawei chips — and most Western...
Three days ago, screenshots from DeepSeek's gray-scale test started circulating on Weibo.
Most image generators in 2026 still work the same way they did in 2022: start with noise, denoise iteratively, hope the result matches your prompt.
NVIDIA dropped Nemotron 3 Super a few weeks ago, and the discourse moved on within 48 hours. Understandable — March was a firehose of model releases.
Every video diffusion model released in the last year has followed the same playbook: train bigger, throw more VRAM at inference, charge accordingly.
Google dropped Gemma 4 on Wednesday — four open-weight models under a genuine Apache 2.0 license, built from the same research behind Gemini 3.
Google shipped Gemma 4 yesterday under Apache 2.
Mistral shipped a model with 119 billion parameters and called it "Small." Under Apache 2.
NVIDIA dropped Nemotron 3 Super a few weeks ago and it flew under the radar — buried by the Mythos leak drama and GPT-5.4's benchmark parade.