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VECTOR WIREAI INTELLIGENCE
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InternVL3.5-1B vs Qwen3 VL 4B Instruct

OpenGVLab

Wins 0 of 1 area

—

Alibaba · released

Wins 1 of 1 area

Images and charts

Qwen3 VL 4B Instruct is the stronger all-rounder.

Scores updated · 6 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 Qwen3 VL 4B Instruct pulls ahead

  • Reads text in imagesOCRBench+54.6points aheadQwen3 VL 4B Instruct88.1InternVL3.5-1B33.5
  • Visual perception tasks people solve at a glanceBLINK+21.6points aheadQwen3 VL 4B Instruct65.8InternVL3.5-1B44.2
  • Questions that truly need the image to answerMMStar+19.5points aheadQwen3 VL 4B Instruct69.8InternVL3.5-1B50.3

Where InternVL3.5-1B pulls ahead

No clear win on a test scored out of 100.

Every test, side by side

All 6 tests both models report. The winning score is in its model's colour; marks a score checked independently.

Images and chartsQwen3 VL 4B Instruct
  • OCRBenchQwen3 VL 4B Instruct by 54.633.588.1+54.6
  • BLINKQwen3 VL 4B Instruct by 21.644.265.8+21.6
  • MMStarQwen3 VL 4B Instruct by 19.550.369.8+19.5

Full images and charts ranking

Other results3 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, InternVL3.5-1B or Qwen3 VL 4B Instruct?

Qwen3 VL 4B Instruct wins the one area where both have results: images and charts. InternVL3.5-1B wins none.

How do you compare the two?

We use the 6 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 3 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.