The available evidence does not show why people have not run Glasshouse. In a September 28, 2026 DEV Community post, its author, woochan, reported 15 GitHub stars and zero submissions, then suggested setup effort, judging costs, and workload size as possible obstacles—not confirmed causes. There is also a release-status mismatch: the post describes a standard run, while the linked repository, viewed October 7, calls v0.1 a draft and says no Glasshouse benchmark has been released. That uncertainty matters before anyone can conclude that users opened the benchmark and abandoned it.
What Glasshouse is meant to measure
Glasshouse is presented as a long-term memory benchmark: a system must retain and retrieve information across a conversation, multiple languages, and photographs. The September 28 post says the workload contains 2,847 questions, covers 10 languages and includes 50 photographs. Those figures describe the author’s account; the current repository does not provide a released benchmark with which to independently verify them.
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The design aims to make memory quality more than a single score. It reports evaluation axes separately and treats uncertainty and contradictory records as behaviors to test. If a stored fact has changed, the expected behavior is to acknowledge uncertainty rather than confidently return an outdated value. If records conflict without resolution, the system should say so.
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What “fair” means in the project’s rules
The repository rules emphasize fixed readers, judges, and prompts, along with public per-question records and a harness intended for customer use. They define three runs as a result and five as certified. The contribution guide asks submitters to provide both a manifest and the per-question record, with enough detail for others to check how a score was produced.
That structure could make comparisons auditable: participants would be judged under specified conditions, and readers could inspect the evidence behind a score. But rules for reproducibility are not the same as a released, runnable benchmark, and they do not establish that any Glasshouse score has been independently reproduced.
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Why might people stop before running it?
In the post, woochan proposes several practical explanations. The author frames them as guesses and asks readers what would need to change. No user interviews, cost comparison, or other evidence establishes that any one of these explains the lack of submissions.
Participants may need to build the ingest path
The author says the project does not ship a benchmark runner for storing the corpus, so participants must implement their own ingest path. That means the task is not necessarily as simple as downloading a benchmark and submitting a result: a prospective participant may first have to connect the evaluation data to a memory system.
Judging uses a paid API
The post says judging runs through OpenRouter using the participant’s own key. It gives no per-run price, so the actual cost cannot be established from the post. API-based judging creates a direct usage-cost question, but the available material does not show how large that cost is in practice.
The reported standard run is large
Woochan reports that a standard run uses 1.97 million tokens. This is an author-reported workload figure, not a repository-verified measurement of a released run. The post also identifies the fixed official reader as “claude-opus-5.5” and characterizes it as not the cheap option; it provides no price calculation or comparison.
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A smaller entry point was suggested, but availability is unclear
A DEV Community commenter suggested publishing baseline runs and offering a small, low-cost introductory split so prospective participants would have a concrete comparison. Woochan replied that a core tier and dry mode existed but had not been mentioned in the post. However, the linked repository currently labels v0.1 a draft, says no Glasshouse benchmark has been released, and shows no submissions. The available information does not establish whether those modes are accessible as a runnable release.
The adoption numbers need a date and a status qualifier
Woochan’s September 28 post reported 15 stars, 0 forks, 0 issues, and 0 submissions. The repository page showed 16 stars when accessed October 7, so the star count changed; these figures should not be treated as a current live tally. More importantly, the repository’s draft status and statement that no benchmark has been released complicate what “0 runs” means: a lack of submissions may reflect an unavailable release, as well as—or instead of—participant disinterest.
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How the project addresses a fairness concern
The repository acknowledges a potential conflict: Wontopos, which administers the benchmark, also builds memory infrastructure in the field the benchmark evaluates. It says Wontopos submissions follow the same process, the host does not approve its own submissions, and published rules govern inclusion and verification. It also invites other memory companies to co-administer.
These are governance safeguards meant to make the conflict visible and constrain the operator’s role. They do not prove that bias is impossible; co-administration and transparent, checkable procedures would be relevant to evaluating how well the safeguards work.
What the evidence can—and cannot—answer
The project has a detailed proposed evaluation and reproducibility framework, but the linked repository’s current description does not establish a released benchmark or a completed run. The author’s explanations for low participation are plausible friction points, not demonstrated causes. Until release status is clarified and participants can run the same accessible version, the question “What’s wrong with it?” remains open.
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Quick Recap
Sources
- Woochan’s DEV Community article, September 28, 2026
- Glasshouse repository
- Glasshouse contribution guide
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