# Nathan Lambert: 'Open artifacts #23' — open-model consolidation isn't happening

> Interconnects #23 argues the open-model field is widening, not consolidating — more labs are training strong open models than predicted.

- Org: Interconnects AI
- Date: 2026-08-02
- Category: article
- Source: https://www.interconnects.ai/p/latest-open-artifacts-23-laguna-s21
- Canonical page: https://ai-tldr.dev/releases/interconnects-open-artifacts-23-aug2/

## In short

Nathan Lambert's Interconnects #23 argues consolidation predicted for 2026 isn't happening. Instead more labs — Thinking Machines' Inkling, Tencent's Hy3, Poolside's Laguna S 2.1 — keep training strong open models.

## What it is

Nathan Lambert and Florian Brand's Aug 2 Interconnects essay catalogs about ten open-model releases from the past month and pushes back on the consolidation thesis. The read: labs are treating token production as a business, and open-model diversity is growing, not shrinking.

## How it works

Interconnects #23 walks through each recent release — Thinking Machines' Inkling (975B-A41B multimodal MoE), Tencent's Hy3 (295B-A21B, Apache 2.0), Poolside's Laguna S 2.1 (118B-A8B, fits on a DGX Spark), Meituan's LongCat-2.0 (1.6T on Ascend 910s), AMD's Instella-MoE (16B-A3B on Instinct cards), Swiss AI's Apertus v1.5 70B, and Motif-3-Beta (314B-A13B) — showing labs spread across the U.S., China, Europe, and specialty accelerators.

## Why it matters

The essay pushes back on the 'consolidation is inevitable' storyline that has framed AI in 2025-26. If Nathan Lambert is right, open-model diversification is the actual pattern — more labs entering the field, more geographies training frontier open weights, and the Pareto frontier widening rather than compressing.

## Who it's for

open-source AI followers, ML researchers, infra leads

## Links

- [Read on Interconnects](https://www.interconnects.ai/p/latest-open-artifacts-23-laguna-s21)
- [Interconnects](https://www.interconnects.ai/)