Qwen3-VL-235B-A22B-Instruct-MXFP4
amd/Qwen3-VL-235B-A22B-Instruct-MXFP4
Tracked by OpenModelStats since September 10, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 7,013
- Total downloadsCumulative all-time download counter reported by the source platform.
- 47.2K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +164(increase)
- 0.4%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 0
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #1137 among tracked Image Text to Text models.
- #9,816
- 124(down 124 places)this week
- Parameters
- 119B
- Last source update
- Jul 27, 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.
- 35.1
- Qwen3-VL-235B-A22B-Instruct-MXFP4 gained 164 downloads during the last seven tracked days.
- It moved from #1118 to #1137 among tracked Image Text to Text models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
Qwen3-VL-235B-A22B-Instruct-MXFP4 is a image text to text model published by amd. OpenModelStats has tracked the model since Sep 10, 2026, most recently observing it 14h ago.
- Published
- Jul 27, 2026
- Last updated
- Jul 27, 2026
- Library
- transformers
- License
- apache-2.0
- Task
- Image Text to Text
- Parameters
- 118,770,576,112
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 23
transformerssafetensorsqwen3_vl_moeimage-text-to-textconversationalarxiv:2505.09388arxiv:2502.13923arxiv:2409.12191arxiv:2308.12966license:apache-2.0endpoints_compatible8-bit
Publisher
amdView publisher statistics →Similar models
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