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VECTOR WIREAI INTELLIGENCE
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Gemini 2.5 Pro vs GLM-4.6V (106B-A12B)

Google · released

Wins 1 of 1 area

Images and charts

Z.ai

Wins 0 of 1 area

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Gemini 2.5 Pro is the stronger all-rounder.

Scores updated · 9 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.

What it costs

Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.

Gemini 2.5 Pro$1.25 to read · $10.00 to write$11Price from Artificial Analysis
GLM-4.6V (106B-A12B)No current price is tracked.

The biggest differences

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

Where Gemini 2.5 Pro pulls ahead

  • College exam questions with charts, maps and diagramsMMMU+4.4points aheadGemini 2.5 Pro79.6GLM-4.6V (106B-A12B)75.2
  • Questions that truly need the image to answerMMStar+3.9points aheadGemini 2.5 Pro79.2GLM-4.6V (106B-A12B)75.3

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

No clear win on a test scored out of 100.

Every test, side by side

All 9 tests both models report. The winning score is in its model's colour; marks a score checked independently.

Images and chartsGemini 2.5 Pro

Full images and charts ranking

Other results5 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, Gemini 2.5 Pro or GLM-4.6V (106B-A12B)?

Gemini 2.5 Pro wins the one area where both have results: images and charts. GLM-4.6V (106B-A12B) wins none.

How do you compare the two?

We use the 9 benchmark tests both models have published scores on. The verdict counts the 4 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 5 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.