GLM-5.2-Int4-Int8Mix
QuantTrio/GLM-5.2-Int4-Int8Mix
Tracked by OpenModelStats since August 31, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 2,422
- Total downloadsCumulative all-time download counter reported by the source platform.
- 99.6K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +595(increase)
- 0.6%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 21
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #4810 among tracked Text Generation models.
- #18,506
- 92(up 92 places)this week
- Parameters
- 785B
- Last source update
- Jun 22, 2026
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 47.6
- GLM-5.2-Int4-Int8Mix gained 595 downloads during the last seven tracked days.
- It moved from #4846 to #4810 among tracked Text Generation models this week.
Downloads over time
Daily gain between consecutive observationsLikes over time
Rank among tracked models
Lower is betterOverview
GLM-5.2-Int4-Int8Mix is a text generation model published by QuantTrio. OpenModelStats has tracked the model since Aug 31, 2026, most recently observing it Sep 30, 2026.
- Published
- Jun 22, 2026
- Last updated
- Jun 22, 2026
- Library
- transformers
- License
- mit
- Task
- Text Generation
- Parameters
- 784,977,079,072
- Spaces
- —
- Derivative models
- 1
- Velocity 7D/day
- 85
transformerssafetensorsglm_moe_dsatext-generationvLLMcompressed-tensorsINT4INT8W4A16W8A16conversationalarxiv:2602.15763
Publisher
QuantTrioView publisher statistics →Derived from zai-org/GLM-5.2 (reported by the source; parent not yet tracked).
Model family
Based on base-model relationships reported by the source's metadata.
Derivative models
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