Comfy-Org/z_image_turbo warn
claims base: Tongyi-MAI/Z-Image-Turbo · chat template: not in config · view on Hugging Face ↗
Ingot findings
Static battery: 1 medium finding(s). Deep battery (behavioral differential, glitch-token pass) not yet run. Weights battery: embedding-norm scan over 151936 tokens (BF16, 2560-dim) found 0 undertrained candidates, 0 plain-ASCII. Lineage vs Tongyi-MAI/Z-Image-Turbo: consistent. Scanned 2026-08-20 (published from a community scan).
medium Repo ships executable Python (trust_remote_code)
The repository contains custom code files that run in-process when loaded with trust_remote_code=True. Pin the revision hash and review the code before loading.
How to fix
Review and pin the custom code; never float on `main` with trust_remote_code=True.
- Read every `.py` file in the repo before first load — this code runs in your process.
- Pin the revision: `from_pretrained(model_id, revision="<commit sha>", trust_remote_code=True)` so a later push can't swap the code under you.
- Prefer a version of the architecture already in `transformers` if one exists, which removes the remote-code requirement entirely.
info Embedding-norm glitch scan clean
No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (1.126). The glitch-token data-corruption class has no candidate surface in this model.
How to fixruntime guardweight-level
Keep the affected token strings out of the model's input — the scan-derived runtime guard carries this model's exact blocklist.
- Fetch this model's guard artifact (`/api/v1/guard/<owner>/<model>`): the confirmed corrupting tokens and the low-norm candidate list, derived from the published scan.
- Screen inbound text with it (the `@ingotai/guard` package is a reference implementation) and route flagged records to a different model or human review — verbatim-copy tasks on flagged strings are the failure mode.
- The underlying cause is undertrained embeddings in the weights; a true fix is weight-level (continued pretraining on the affected tokens) — that is not a patch, it's a training job.
info Weights consistent with claimed parent Tongyi-MAI/Z-Image-Turbo
Mean cosine similarity of 64 sampled token-embedding rows against Tongyi-MAI/Z-Image-Turbo is 1.000 — the weights plausibly descend from the declared base (relation: unspecified).
How to fix
Fix or verify the `base_model` declaration so lineage checks can run.
- If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
- If you don't: identify the true parent (config architecture + weight shapes narrow it fast) and re-scan with that lineage in mind.
Remediation guidance addresses the documented findings only. It is evidence-driven repair, not a safety certification of the model.
Fingerprint
The durable weights-and-metadata profile of this model, rebuilt on every scan and deep-battery run. Updated 2026-08-20.
| vocabulary | 151,936 tokens |
| license | apache-2.0 |
| serialization | safetensors custom code |
| chat template | none |
| claimed lineage | Tongyi-MAI/Z-Image-Turbo |
| lineage verified | consistent vs Tongyi-MAI/Z-Image-Turbo — embedding-row cosine 1.000 |
| glitch-token surface | clean no undertrained tokens |
Full fingerprint
| library | diffusion-single-file |
| repo files | 11 |
| revision | 08d044552790 |
| HF snapshot | 6.1M downloads · 822 likes · updated 2026-08-17 · captured 2026-08-20 |
| embedding tensor | model.embed_tokens.weight · BF16 · 151,936×2560 |
| embedding norms | median 1.1262 · mean 1.0974 |
| lineage check | consistent — cosine 1 over 64 sampled rows vs Tongyi-MAI/Z-Image-Turbo |
Verdict badge
Ship the verdict in your README — it always shows the latest published analysis:
[](https://ingot.tools/models/Comfy-Org/z_image_turbo)