For the first time in the MLPerf inference benchmarks, AMD posted numbers that don't require mental gymnastics to interpret.
A 3.4 GB model just posted a 97.
Google shipped Gemma 4 yesterday under Apache 2.
I spent three months in 2024 building retry logic for a pipeline that extracted product data from GPT-4.
Alibaba dropped Qwen 3.6-Plus this week, and the headline number caught my attention: 61.
Every quarter, someone on the team asks: "Do we really need this Spark cluster?" For most of the jobs running on it, the answer in 2026 is no.
Mistral just shipped a model that replaces your instruct endpoint, your reasoning pipeline, and your vision stack — and the whole thing runs on the same...
OpenAI dropped GPT-5.4 on March 5, and the headline number — 75% on OSWorld-Verified, beating the 72.
Everyone picks their vector database based on latency benchmarks and API ergonomics.
You've been debugging your prompt for an hour. You've tried different phrasings, added examples, restructured the whole thing.
The open-weight leaderboard has a new king, and you probably can't afford to host it.