Mathematics · DeepSeek

DeepSeek-V3.2 on AIME 2025: score, rank and what it means

DeepSeek-V3.2 scores 79.6 on AIME 2025, placing it #93 of 600 models in the index. The benchmark average is 63.6 and the leader is Claude Opus 4.5 Pro at 91.4.

Score
79.6
0–100 scale
Rank
#93
of 600
Percentile
85th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
11.8
points

Score distribution

The chart shows the top 10 models on AIME 2025, with DeepSeek-V3.2 highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Pro 91.4
GPT-5.2 Pro 91.0
GPT-5.1 Pro 90.6
GPT-5.2 90.6
o4 Reasoning 90.3
o4 Pro 89.9
Claude Opus 4.5 89.8
Gemini 3 Pro Max 89.6
Claude Opus 4.5 Max 89.3
Claude Opus 4.5 Reasoning 88.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 GPT-5.2 OpenAI 2000000 $19.71 88.0
5 o4 Reasoning OpenAI 1000000 $19.69 87.5
6 o4 Pro OpenAI 1000000 $19.37 87.3
7 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
8 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On AIME 2025, DeepSeek-V3.2 sits at #93 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 11.8 points. The median model in this index scores 67.6, which puts DeepSeek-V3.2 above the midpoint.

DeepSeek models average 65.1 on this benchmark. DeepSeek-V3.2 is 14.5 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among frontier models, the average is 84.9. DeepSeek-V3.2 is 5.3 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 79.6 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $5.88 per million input tokens, DeepSeek-V3.2 is above the median input price of $4.00 across the 600 models scored on AIME 2025. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GPT-4.1 OpenAI 1000000 $15.71 82.4
Gemini 3 Flash Pro Google DeepMind 400000 $17.71 84.8
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7
Claude 3.7 Sonnet Reasoning Anthropic 128000 $16.30 83.7
DeepSeek-V3.2 DeepSeek 1000000 $5.88 84.0
Llama 4 Maverick Meta AI 200000 $5.36 81.6
ERNIE 4.5 Max Baidu 128000 $14.41 80.6

Other benchmarks for DeepSeek-V3.2

BenchmarkScoreRankPercentileRelative
MMLU-Pro 86.9 37 94th
GPQA Diamond 79.7 63 90th
SWE-bench Verified 74.4 47 92th
HumanEval 89.7 53 91th
MATH-500 89.7 52 91th
LiveCodeBench 80.4 40 93th
IFEval 89.4 77 87th
TruthfulQA 84.5 73 88th
HellaSwag 90.2 78 87th
MMMU 79.9 57 91th
Arena Elo 1455.6 62 90th

FAQ

What score does DeepSeek-V3.2 get on AIME 2025?

DeepSeek-V3.2 scores 79.6 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

How does DeepSeek-V3.2 rank on AIME 2025?

It ranks #93 of 600 models, in the 85th percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is DeepSeek-V3.2 good at AIME 2025?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the AIME 2025 score calculated?

AIME 2025 is a mathematics benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does DeepSeek-V3.2 cost?

DeepSeek-V3.2 costs $5.88 per million input tokens and $24.70 per million output tokens.

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