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Support · GLM

Will it last?

Ownership levelPartialnone·limited·partial·substantial·fullAnalytical input C · 65.2/100

This page is a projection of the one entry record, the Transparency factor that Support covers. The full verdict is set by all four factors together, floor-weighted so the weakest caps the whole.

Which domain expands which factor
  • AssessUse & modify + Transparency
  • ImplementData control + Doesn't fail you
  • UseDoesn't fail you
  • SupportTransparency

Common problems & fixes

Aggregated common pitfalls (not an exhaustive catalogue):

  • Out-of-memory on the MoE. The 355B/106B MoE hold their full parameter count in memory even at 32B/12B active - use a smaller variant, quantize, or move to a multi-GPU node; reduce max context to shrink the KV cache at the 200K window.
  • Garbled or over-verbose output. You are almost certainly not applying the chat template or are mishandling the thinking/agentic mode - use apply_chat_template.
  • Checksum drift across hubs. The dual Hugging Face (zai-org) / ModelScope distribution means checksums must match; a mismatch signals a stale mirror or the legacy THUDM org.
  • Wrong-LICENSE assumption. Not every GLM checkpoint is MIT - the original glm-4-9b is custom-licensed; read the LICENSE on the exact model.
  • Non-reproducible results. You floated on main; pin an exact revision.

Versions, changelog & cadence

Releases follow a rapid cadence - GLM-4-0414 → GLM-4.5 / GLM-4.5-Air → GLM-4.6 - rather than a rolling semantic-version stream. Individual versions are tracked as immutable Hugging Face / ModelScope revisions on the verified zai-org org, so the revision hash is your changelog anchor: pin it, and diff against a newer revision when you choose to upgrade. GitHub repositories (zai-org/GLM-4, zai-org/GLM-4.5) and technical reports accompany the releases.

Newer variants occasionally referenced elsewhere (GLM-5, GLM-4.7, GLM-4.6V) are not verified in this entry and are deliberately omitted; anchor to GLM-4.6 as the current confirmed flagship.

Community & support channels

  • Hugging Face model discussion tabs on the zai-org org (ev-hf-zai) for usage questions.
  • ModelScope org discussions (ev-modelscope) for the China-facing community.
  • GitHub issues on the zai-org/GLM-4 and zai-org/GLM-4.5 repositories (ev-github) for inference-code and integration problems.

There is no paid support tier around the open weights - this is community and maintainer support (Zhipu also offers a separate commercial hosted API under the Z.ai brand).

Tracked known issues

Drawn from model-card and third-party caveats rather than a formal issue tracker (hence partial):

  • China-aligned alignment and hosted-API content moderation on politically sensitive topics.
  • Safety tuning is lighter than the large Western labs, with no companion guard model.
  • Capability leadership is concentrated in coding/agentic rather than uniform.
  • An unresolved EU systemic-risk / Article 55 question on the 355B MoE, with no published documentation.

How this scores

The ownership factor this domain covers, drawn from the one entry record.

2

TransparencyDo you know what it is: weights, training, behaviour, and legible terms?

Weak

You hold the weights but cannot see what they are: training data and training code are closed, the models carry China-aligned alignment you cannot inspect, and the hosted Z.ai API applies Chinese content moderation.

How this scores (AOI sub-dimensions)
Provenance3/5how well we can trace and verify what went into the modelVerified zai-org on Hugging Face plus official ModelScope publication, safetensors with checksums, and no canonical-org malicious incident (checklist 5/8).
Governance3/5how accountable and well-documented the publisher isActive, accountable publisher (Zhipu AI / Z.ai) with a rapid release cadence and a verified presence on Hugging Face and ModelScope, but no documented vulnerability-disclosure or deprecation policy and no EU Code of Practice signature.
What this means for adoptionYou substantially - but not uniformly - own the GLM line, and the split is per-variant. The current line is genuine MIT: GLM-5.2 ships a real checked-in MIT LICENSE ('Copyright (c) 2026 Zhipu AI') and the GLM-4.5/4.6 and GLM-4-0414 siblings declare the same MIT via HF metadata/README, so you can run, fine-tune, distill, redistribute and commercialise them with no gate. The caveat is the legacy glm-4-9b - NOT plain MIT but a custom 'glm-4' licence requiring commercial-use registration, 'Built with glm-4' attribution and a name prefix, governed by PRC law with disputes to Beijing's Haidian District court - so verify the LICENSE per checkpoint. Two things hold it at partial: training is opaque (closed data/code, China-aligned alignment you cannot inspect) and no safety battery is benchmarked, so supply your own guards. Mind the jurisdiction split too - the weights you self-host are yours, but the hosted Z.ai service is Singapore-governed (SIAC arbitration), a different legal regime from the PRC glm-4-9b weights licence; do not conflate the two.

Sources

The same evidence records as the entry sheet. Read means the text was verified; unverified means it is known to exist but not yet read.

Model cardread2026-07-25
GLM-4.6 is a 355B-total / 32B-active MoE with a 200K context window, released by Zhipu AI / Z.ai and hosted on the zai-org Hugging Face org; the model card/metadata declares MIT.
Model cardread2026-07-25
GLM-4.5 (355B/32B) and GLM-4.5-Air (106B/12B) are MoE models on the zai-org Hugging Face org; the GLM-4.5 README states "They are released under the MIT open-source license and can be used commercially and for secondary development."
Model cardread2026-07-25
GLM checkpoints are hosted on the verified zai-org org on Hugging Face in safetensors with checksums (the current org; legacy checkpoints are under THUDM).
Licenceread2026-07-25
The GLM-4.5, GLM-4.6 and GLM-4-32B-0414 checkpoints declare the OSI-approved MIT license permitting commercial use - but via HF metadata ("License: mit") and README only; there is NO in-repo LICENSE file (raw/blob LICENSE returns 404).
Licenceread2026-07-25
GLM-5.2 ships a REAL in-repo MIT LICENSE file, read verbatim: standard MIT text with no custom clauses, "Copyright (c) 2026 Zhipu AI." This resolves the metadata-only gap on the 4.5/4.6/0414 line by confirming the family MIT is a genuine, checked-in MIT licence on at least one current sibling.
Licenceread2026-07-25
Licensing is per-variant and the legacy glm-4-9b is NOT plain MIT.
Documentationunverified2026-07-25
The GLM-4-0414 family (dense GLM-4-32B-0414 and GLM-4-9B-0414, up to 128K extended context) was open-sourced under the MIT license.
Documentationunverified2026-07-25
Zhipu / Z.ai publishes GLM inference code and technical reports on GitHub (zai-org/GLM-4, zai-org/GLM-4.5), but not the training data or training pipeline.
Model cardunverified2026-07-25
GLM models are also officially published on Alibaba's ModelScope hub (dual distribution) by Zhipu.
Terms of serviceread2026-07-25
Hosted Z.ai Terms of Service, read verbatim: governed by Singapore law with SIAC arbitration (seat Singapore).
Privacy Policyread2026-07-25
Hosted Z.ai Privacy Policy, read verbatim: data is processed in Singapore; API content is "not saved on our servers"; consumer content is used "when we train and improve our models." The Singapore processing location is distinct from the PRC jurisdiction of the glm-4-9b weights licence.
Third-party analysisunverified2026-07-25
Third-party evaluation places GLM-4.6 among the stronger open models for real-world coding, tool use and agentic tasks.
Third-party analysisunverified2026-07-25
GLM models carry China-aligned alignment and the hosted Z.ai API applies Chinese content moderation on politically sensitive topics.
Third-party analysisunverified2026-07-25
GLM is supported for local serving on vLLM and SGLang (with community GGUF quants for the dense sizes) and distributed across Hugging Face and ModelScope.
Third-party analysisunverified2026-07-25
GLM instruct variants are safety-tuned but with lighter alignment coverage than Western frontier labs and no companion guard model.
Model cardunverified2026-07-25
No public EU AI Act training-content summary, copyright policy, or Article 55 documentation is published for GLM, and the 355B MoE's systemic-risk status is unconfirmed.