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VECTOR WIREAI INTELLIGENCE
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GLM-4.6V (106B-A12B) vs Qwen3 VL 4B (Reasoning)

Z.ai

Wins 1 of 1 area

Images and charts

Alibaba · released

Wins 0 of 1 area

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GLM-4.6V (106B-A12B) is the stronger all-rounder.

Scores updated · 7 tests both models report · How we compare

Where each one wins

Tests won in each of the one area where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.

The biggest differences

The tests each model wins by the widest margin, up to three each. Scores are out of 100.

Where GLM-4.6V (106B-A12B) pulls ahead

  • Reads text in imagesOCRBench+5.4points aheadGLM-4.6V (106B-A12B)86.2Qwen3 VL 4B (Reasoning)80.8
  • Math problems shown in pictures and chartsMathVista+4points aheadGLM-4.6V (106B-A12B)83.5Qwen3 VL 4B (Reasoning)79.5
  • Questions that truly need the image to answerMMStar+2.1points aheadGLM-4.6V (106B-A12B)75.3Qwen3 VL 4B (Reasoning)73.2

Where Qwen3 VL 4B (Reasoning) pulls ahead

No clear win on a test scored out of 100.

Every test, side by side

All 7 tests both models report. The winning score is in its model's colour; marks a score checked independently.

Images and chartsGLM-4.6V (106B-A12B)
  • OCRBenchGLM-4.6V (106B-A12B) by 5.486.280.8+5.4
  • MathVistaGLM-4.6V (106B-A12B) by 483.579.5+4
  • MMStarGLM-4.6V (106B-A12B) by 2.175.373.2+2.1

Full images and charts ranking

Other results4 tests, not counted

Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.

Questions people ask

Which is better, GLM-4.6V (106B-A12B) or Qwen3 VL 4B (Reasoning)?

GLM-4.6V (106B-A12B) wins the one area where both have results: images and charts. Qwen3 VL 4B (Reasoning) wins none.

How do you compare the two?

We use the 7 benchmark tests both models have published scores on. The verdict counts the 3 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 4 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.