Qwen3-VL-4B-Instruct qwen3-vl-4b-instruct
qwen · qwen vision efficient
#105 overall
- params
- 4.4B
- arch
- dense
- license
- apache-2.0 open weights
# architecture
- layers
- 36
- d_model
- 2560
- heads
- 32q / 8kv
- head dim
- 128
- vocab
- 151936
- family
- qwen3_vl_text
signal path of one layer, generated from the registry's structured fields — dimension lines quote the model's real numbers; an MoE trace forks at the router, a dense trace runs straight through. Geometry fields come from the repo's config.json.
# why ranked
Overall: #105 — score 5.6 ● high — all signals present
| signal | weight | input (0–100) |
|---|---|---|
| aa_intelligence | 0.70 | 4.9 |
| bench_composite | 0.30 | 7.4 |
benchmark panel evidence:
| complete panel | score (0–100) |
|---|---|
| aa-math-v1 | 14.8 |
| aime-2025-v1 | 0.0 |
# trend
methodology changed during this history window; score movement across that boundary is not model movement. See methodology v6.
# benchmarks
| benchmark | score | source | date |
|---|---|---|---|
| AA Intelligence Index | 5.7 | Artificial Analysis | — |
| AA Math Index | 37.0 | Artificial Analysis | — |
| Ai2d | 0.8 / 1 | LLM Stats | — |
| AIME 2025 | 0.5 / 1 | LLM Stats | — |
| Bfcl-v3 | 0.6 / 1 | LLM Stats | — |
| Blink | 0.7 / 1 | LLM Stats | — |
| Cc-ocr | 0.8 / 1 | LLM Stats | — |
| Charadessta | 0.6 / 1 | LLM Stats | — |
| Charxiv-d | 0.8 / 1 | LLM Stats | — |
| Charxiv-r | 0.4 / 1 | LLM Stats | — |
| Mm-mt-bench | 7.5 | LLM Stats | — |
# where to run
no known API providers — download the weights from Hugging Face and run them yourself.
source aliases
- aa
qwen3-vl-4b-instruct- llmstats
qwen3-vl-4b-instruct