Reasoning · DeepSeek

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

DeepSeek-R1 Base scores 76.2 on GPQA Diamond, placing it #114 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
76.2
0–100 scale
Rank
#114
of 600
Percentile
81th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
10.8
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with DeepSeek-R1 Base 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 Base sits at #114 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 10.8 points. The median model in this index scores 68.8, which puts DeepSeek-R1 Base above the midpoint.

DeepSeek models average 67.5 on this benchmark. DeepSeek-R1 Base is 8.7 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 Base is 2.7 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 76.2 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 $5.05 per million input tokens, DeepSeek-R1 Base 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
ERNIE 4.0 Max Baidu 32768 $12.40 78.9
ERNIE 4.5 Max Baidu 128000 $14.41 80.6
Command A Reasoning Cohere 400000 $13.74 80.2
Claude Opus 4.5 Mini Anthropic 65536 $12.72 79.0
DeepSeek-R1 Base DeepSeek 400000 $5.05 80.1
ERNIE 4.0 Turbo Baidu 65536 $12.00 78.0
Sonar Pro Reasoning Perplexity 128000 $13.94 80.5

Other benchmarks for DeepSeek-R1 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.0 147 76th
SWE-bench Verified 71.2 91 85th
HumanEval 83.4 149 75th
MATH-500 84.9 109 82th
AIME 2025 73.8 189 69th
LiveCodeBench 76.0 82 86th
IFEval 88.2 97 84th
TruthfulQA 82.2 126 79th
HellaSwag 90.0 85 86th
MMMU 74.2 178 70th
Arena Elo 1442.9 94 84th

FAQ

What score does DeepSeek-R1 Base get on GPQA Diamond?

DeepSeek-R1 Base scores 76.2 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does DeepSeek-R1 Base rank on GPQA Diamond?

It ranks #114 of 600 models, in the 81st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is DeepSeek-R1 Base 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 Base cost?

DeepSeek-R1 Base costs $5.05 per million input tokens and $26.24 per million output tokens.

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