DeepSeek-V3.2 is the stronger all-rounder.
Scores updated · 5 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.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where DeepSeek-V3.2 pulls ahead
- Harvard-MIT high-school math contest problemsHMMT Feb. 2026+19.7points ahead
- US invitational high-school math exam problemsAIME 2026+11.7points ahead
Where QED-Nano pulls ahead
No clear win on a test scored out of 100.
Every test, side by side
All 5 tests both models report. The winning score is in its model's colour; marks a score checked independently.
MathDeepSeek-V3.2
- HMMT Feb. 2026DeepSeek-V3.2 by 19.784.164.4+19.7
- AIME 2026DeepSeek-V3.2 by 11.794.282.5+11.7
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.
- HMMT Feb. 2025DeepSeek-V3.2 by 15.892.576.7+15.8
- AIME 2025DeepSeek-V3.2 by 15.693.177.5+15.6
- HMMT Nov. 2025DeepSeek-V3.2 by 159075+15
Questions people ask
Which is better, DeepSeek-V3.2 or QED-Nano?
DeepSeek-V3.2 wins the one area where both have results: math. QED-Nano wins none.
How do you compare the two?
We use the 5 benchmark tests both models have published scores on. The verdict counts the 2 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.