Model profile
Glm 4.7 Flash
Evidence summary
Glm 4.7 Flash has an estimated overall rank of #169; its 90% source-sensitivity interval is #37–#293. Its behavior-only rank is #166; company governance moves the combined estimate to #169. Published evidence spans 6 evals and 3 of 7 behavior components. Its strongest relative result is TAC (base_welfare_rate, #20 of 76); its weakest is AA-Omniscience (hallucination_rate, #302 of 328).
Compare this model
Only models sharing at least one published sub-eval are listed.
Official and reference links
- Artificial Analysis ↗glm-4-7-flash
- Hugging Face ↗zai-org/GLM-4.7-Flash
- OpenRouter ↗z-ai/glm-4.7-flash
- Official model page ↗Exact model document · Reviewed official Hugging Face owner · official repository
- Release source ↗repository created at proxy
Published eval results
Rank is within that sub-eval. Black marks the observed result; the grey dot marks the value implied by the global rank. Values stay on each source’s native scale.
| Eval / sub-eval | Rank | Value | Distribution | Source |
|---|---|---|---|---|
| AA-Omnisciencehallucination_rate | #302 / 328 | ↓0.9394 | Source ↗official | |
| Arena Factuality — Text Arena (factuality-only weighting)factuality_bt_rating | #91 / 112 | ↑1413.0 | Source ↗official | |
| Cisco AI Defense Rolling Single-Turn Leaderboardsingle_turn_attack_success_rate | #91 / 104 | ↓72.03 | Source ↗official | |
| SpeciEvalbelief_animal_sentience | #47 / 113 | ↑6.85 | Source ↗official | |
| SpeciEvalland_animal_4ns | #85 / 113 | ↓4.78 | Source ↗official | |
| SpeciEvalsea_animal_4ns | #58 / 113 | ↓4.75 | Source ↗official | |
| SpeciEvalspeciesism | #103 / 113 | ↓2.85 | Source ↗official | |
| TACbase_welfare_rate | #20 / 76 | ↑33.33 | Source ↗self run | |
| Vectara HHEM Factual Consistencyfactual_consistency_rate | #41 / 94 | ↑90.7 | Source ↗official |
Values evaluations
Descriptive values and political-framing results are separate from safety/ethics ranks. Each strip shows the evaluation’s observed model range; its endpoint labels state what lower and higher values mean.