Mathematics · DeepSeek

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

DeepSeek-V3.2 Chat scores 81.0 on AIME 2025, placing it #75 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
81.0
0–100 scale
Rank
#75
of 600
Percentile
88th
within the index
Benchmark avg
63.6
all models
Leader
91.4
Claude Opus 4.5 Pro
Gap to leader
10.4
points

Score distribution

The chart shows the top 10 models on AIME 2025, with DeepSeek-V3.2 Chat 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 Chat sits at #75 of 600. The leader, Claude Opus 4.5 Pro, scores 91.4, so the gap to the top is 10.4 points. The median model in this index scores 67.6, which puts DeepSeek-V3.2 Chat above the midpoint.

DeepSeek models average 65.1 on this benchmark. DeepSeek-V3.2 Chat is 15.9 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among multimodal models, the average is 73.9. DeepSeek-V3.2 Chat is 7.1 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 81.0 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 $5.80 per million input tokens, DeepSeek-V3.2 Chat 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
Qwen3-Max Turbo Alibaba Cloud 1000000 $17.70 84.7
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
Grok 3 xAI 128000 $15.84 82.8
Qwen3-Max Alibaba Cloud 400000 $17.37 84.4
DeepSeek-V3.2 Chat DeepSeek 1000000 $5.80 82.5
Claude 3.7 Sonnet Vision Anthropic 400000 $13.96 81.0
Kimi K1.5 Moonshot AI 128000 $5.19 80.7

Other benchmarks for DeepSeek-V3.2 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.5 114 81th
GPQA Diamond 78.0 85 86th
SWE-bench Verified 69.6 120 80th
HumanEval 87.9 74 88th
MATH-500 90.2 46 92th
LiveCodeBench 77.9 65 89th
IFEval 88.6 91 85th
TruthfulQA 86.3 45 93th
HellaSwag 89.2 107 82th
MMMU 76.0 140 77th
Arena Elo 1462.2 48 92th

FAQ

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

DeepSeek-V3.2 Chat scores 81.0 on AIME 2025 in this index. The benchmark average is 63.6 and the top score is 91.4.

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

It ranks #75 of 600 models, in the 88th percentile. The leader is Claude Opus 4.5 Pro at 91.4.

Is DeepSeek-V3.2 Chat 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 Chat cost?

DeepSeek-V3.2 Chat costs $5.80 per million input tokens and $26.43 per million output tokens.

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