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google/gemma-4-31B-it-qat-w4a16-ct pass

downloads 1.7Mlikes 60license apache-2.0arch gemma4params 33597.6Mupdated 2026-07-20

claims base: google/gemma-4-31B-it-qat-q4_0-unquantized · chat template: present · view on Hugging Face ↗

Scan coverage

Ingot runs three batteries against a model. What each one checks →

BatteryLooks atStatus
Static batteryMetadata & packagingcomplete 2026-08-22
Weights batteryWeights forensics — no GPU, no downloadcomplete 2026-08-22262,144-token embedding scanned · 0 undertrained · lineage consistent
Behavioral batteryLive-inference differentialsnot run

Findings

Scanned 2026-08-22 · published from a community scan.

info Embedding-norm glitch scan clean

No undertrained tokens found: every non-special token's embedding norm is above 0.3× the vocabulary median (0.984). The glitch-token data-corruption class has no candidate surface in this model.

info Weights consistent with claimed parent google/gemma-4-31B-it-qat-q4_0-unquantized

Mean cosine similarity of 64 sampled token-embedding rows against google/gemma-4-31B-it-qat-q4_0-unquantized 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.

  1. If you own the repo: correct the `base_model` field in the model card metadata to the real, public parent.
  2. 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 profile of this model: measured weights-and-metadata facts, rebuilt on every scan and battery run. Updated 2026-08-22.

architecturegemma4 · 5376-dim
parameters33597.6M
vocabulary262,144 tokens
licenseapache-2.0
serializationsafetensors
chat templatenone
claimed lineagegoogle/gemma-4-31B-it-qat-q4_0-unquantized
lineage verifiedconsistent vs google/gemma-4-31B-it-qat-q4_0-unquantized — embedding-row cosine 1.000
glitch-token surfaceclean no undertrained tokens
Full measured fingerprint
architecturesGemma4ForConditionalGeneration
librarytransformers
pipelineimage-text-to-text
repo files9
revision52f3f65bc7a0
HF snapshot1.7M downloads · 59 likes · updated 2026-07-20 · captured 2026-08-21
embedding tensormodel.language_model.embed_tokens.weight · BF16 · 262,144×5376
embedding normsmedian 0.9837 · mean 0.9838
lineage checkconsistent — cosine 1 over 64 sampled rows vs google/gemma-4-31B-it-qat-q4_0-unquantized

Battery runs

The run trace behind the findings above: every deep-battery job for this model, with what each run measured or why it failed. Findings are only as good as the runs that produced them.

batterystatusqueueddurationattempts
weightscomplete2026-08-21 07:423m1
weights run 2026-08-21 measurements
probes runglitch-norm-scan, lineage-norm-correlation
embedding tensormodel.language_model.embed_tokens.weight · BF16 · 262,144×5376
glitch surface0 undertrained, 0 plain-ASCII
lineage checkconsistent — cosine 1 over 64 rows vs google/gemma-4-31B-it-qat-q4_0-unquantized

Verdict badge

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Ingot verdict: pass

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