Reasoning · DeepSeek

DeepSeek-R1 on GPQA Diamond: score, rank and what it means

DeepSeek-R1 scores 77.8 on GPQA Diamond, placing it #89 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
77.8
0–100 scale
Rank
#89
of 600
Percentile
85th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
9.2
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with DeepSeek-R1 highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, DeepSeek-R1 sits at #89 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 9.2 points. The median model in this index scores 68.8, which puts DeepSeek-R1 above the midpoint.

DeepSeek models average 67.5 on this benchmark. DeepSeek-R1 is 10.3 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among multimodal models, the average is 73.5. DeepSeek-R1 is 4.3 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 77.8 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 $5.83 per million input tokens, DeepSeek-R1 is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-V3.2 Chat DeepSeek 1000000 $5.80 82.5
Gemini 2.5 Pro Vision Google DeepMind 200000 $14.91 82.0
Reka Core Pro Reka AI 65536 $13.44 79.9
Qwen3-Coder Alibaba Cloud 200000 $4.94 79.5
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
GPT-4.1 Reasoning OpenAI 1000000 $16.97 83.8
MiniMax-M2 Chat MiniMax 200000 $5.02 80.2

Other benchmarks for DeepSeek-R1

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.8 85 86th
SWE-bench Verified 72.2 73 88th
HumanEval 86.4 97 84th
MATH-500 89.1 55 91th
AIME 2025 81.1 72 88th
LiveCodeBench 77.4 70 88th
IFEval 91.0 53 91th
TruthfulQA 82.9 107 82th
HellaSwag 89.8 90 85th
MMMU 79.5 66 89th
Arena Elo 1454.1 65 89th

FAQ

What score does DeepSeek-R1 get on GPQA Diamond?

DeepSeek-R1 scores 77.8 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does DeepSeek-R1 rank on GPQA Diamond?

It ranks #89 of 600 models, in the 85th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is DeepSeek-R1 good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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-R1 cost?

DeepSeek-R1 costs $5.83 per million input tokens and $25.23 per million output tokens.

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