Coding · DeepSeek

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

DeepSeek-R1 Base scores 76.0 on LiveCodeBench, placing it #82 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
76.0
0–100 scale
Rank
#82
of 600
Percentile
86th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
9.1
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, DeepSeek-R1 Base sits at #82 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 9.1 points. The median model in this index scores 64.7, which puts DeepSeek-R1 Base above the midpoint.

DeepSeek models average 63.4 on this benchmark. DeepSeek-R1 Base is 12.6 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among multimodal models, the average is 70.3. DeepSeek-R1 Base is 5.7 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 76.0 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 $5.05 per million input tokens, DeepSeek-R1 Base is above the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Grok 3 Turbo xAI 128000 $15.97 83.1
o3 Max OpenAI 2000000 $17.82 84.8
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
Gemini 2.5 Pro Google DeepMind 200000 $15.20 81.6
DeepSeek-R1 Base DeepSeek 400000 $5.05 80.1
Gemini 2.5 Pro Vision Google DeepMind 200000 $14.91 82.0
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7

Other benchmarks for DeepSeek-R1 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.0 147 76th
GPQA Diamond 76.2 114 81th
SWE-bench Verified 71.2 91 85th
HumanEval 83.4 149 75th
MATH-500 84.9 109 82th
AIME 2025 73.8 189 69th
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 LiveCodeBench?

DeepSeek-R1 Base scores 76.0 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does DeepSeek-R1 Base rank on LiveCodeBench?

It ranks #82 of 600 models, in the 86th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is DeepSeek-R1 Base good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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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