The Hallway Track

open-weight-models

10 tracked signals on open-weight-models.

The current balance of power in open models

Nathan Lambert · Interconnects · Sep 21, 2026

Chinese open-weight models like GLM-5.2 and Kimi K3 have surpassed American ones and reached commercial agentic viability.

“Since about April 2025, Chinese AI companies have been the clear leader in open-weight models.”
The Cyber Risk Discourse is Broken

Nathan Lambert · Interconnects · Oct 06, 2026

Banning open-weight models will hurt US AI competitiveness while increasing long-term cyber risk

“I feel we're going to end up making policy decisions that both limit American AI competitiveness and increases long-term cyber risk.”
Introducing Kimi K3 on Amazon Bedrock

AWS Machine Learning Blog · Sep 18, 2026

Moonshot AI's Kimi K3, a 2.8-trillion-parameter open-weight model, is now available on Amazon Bedrock.

“Kimi K3 is its most capable model and the first open model to reach 2.8 trillion parameters.”
[AINews] not much happened today

Greg Brockman · Latent Space Blog · Jul 18, 2026

Kimi K3 shifts AI competitive narrative from compute moats to efficiency stacks, pressuring US labs.

“Kimi K3 is really, really good”
Use open weight models as your AI coding agent with Amazon Bedrock

AWS Machine Learning Blog · Sep 23, 2026

Open weight models on Amazon Bedrock let developers run private, pay-per-use AI coding agents like OpenCode.

“What if you could run an AI coding agent that keeps your data in your own AWS account, switches between frontier open weight models on demand, and charges only for what you consume?”
How OneAdvanced deployed over 50 AI agents on UK-sovereign AWS

AWS Machine Learning Blog · Aug 12, 2026

OneAdvanced self-hosted Llama 4 on UK-sovereign AWS to deploy 50+ AI agents for regulated industries.

“Data sovereignty, particularly in the UK, is a hard requirement for many of our customers, especially those in the public sector and highly regulated industries. They need to know exactly where their data is, who has access to it, and that it resides within the UK's legal and regulatory framework to support total compliance and trust.”
Stop writing longer prompts. Do this instead! 🧠

Google Developers (Google I/O) · Jun 24, 2026

Use dataset distillation and fine-tuning instead of longer prompts to enforce consistent structured outputs.

“Prompting tells the model what you want right now. Fine-tuning teaches the model a pattern it can follow repeatedly.”