2026-10-11 16:38 UTC

The live open training run of a 535B-parameter, 23B-active mixture-of-experts model will publish usable checkpoints, training details, and results sufficient for outside scrutiny of the training process.

state: watchingheat: lowuncertainty: highconvergesscott: mediumopen-models model-training mixture-of-expertsPercy Liang

What is this?

The case describes a live, openly observable training run for a 535B-total-parameter mixture-of-experts language model with 23B parameters active during inference, reportedly associated with Marin and announced by Percy Liang. It promises checkpoints, training details, and results that outsiders could inspect; the supplied background confirms that MoE models route tokens through only a subset of parameters and that comparable open projects publish code, data, logs, and intermediate checkpoints. However, the search snippets do not directly document this specific run, its organizers, release terms, or whether the promised artifacts will be sufficient for reproducibility rather than limited scrutiny.

Why it matters to Scott

The proposed run operationally converges with Scott’s Auditability and Provenance-Coupled Work positions by treating checkpoints, logs, training details, and results as part of the model deliverable rather than releasing weights alone; at frontier scale, that also bears on Sovereign Software Assurance’s distinction between nominal openness and demonstrated independent capability. It is a meaningful dated-receipts opportunity if the artifacts enable outside reconstruction, but the supplied evidence does not yet establish that the promised releases will be complete or reproducible.
ip:concept.auditabilityip:framework.provenance-coupled-workip:framework.sovereign-software-assuranceradar:concept.open-model-trainingradar:concept.open-modelsradar:concept.model-provenanceradar:concept.mixture-of-experts
queries asked of Scott's wikis
  • open training runs and process transparency
  • open weights versus full training reproducibility
  • intermediate checkpoints as research infrastructure
  • frontier-scale open model sovereignty
  • MoE training economics and local inference
  • auditable training logs and dataset provenance

Measured heat

now 0 pts/hpeak 3 pts/hcomments 0/hpeers p14momentum: steady2 platformsage 1322h
points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

08-17 14:00⭐ origin echo-reconstructedThe earliest primary artifact found is Marin’s GitHub issue, opened Aug. 18, 2026—before Percy Liang’s Aug. 21 announcement. It says: “Issue
Larry Dial (ClassicLarry), Marin community on github (echo) · attributed from hn.story.49404471
—
08-22 22:27first on hacker news · published · +128.5hFollow live the open training of a 535B (23B activated) LLM
ggcr
—
08-22 22:27amplified on hacker newshn.story.49404471
ggcr
peak 1 · 1 comments · 28% of case engagement
09-04 06:48amplified on hacker newshn.story.49561323
tosh
peak 2 · 0 comments · 28% of case engagement
10-07 03:04amplified on hacker news 👑hn.story.49987571
gmays
peak 3 · 0 comments · 43% of case engagement
08-22 23:21our radar first saw it · +129.3hdiscovery anchor: hn.story.49404471—

Evidence (4) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟧 hnFollow live the open training of a 535B (23B activated) LLMggcr11
🟧 echo.github ⭐The earliest primary artifact found is Marin’s GitHub issue, opened Aug. 18, 2026—before Percy Liang’s Aug. 21 announcement. It says: “IssueLarry Dial (ClassicLarry), Marin community——
🟧 hnMarin 535B-A23Btosh20
🟧 hnOlmo-core 3: Open, scalable training infrastructure for large MoEsgmays30

Interpretation history

Decision trace