Reasoning · DeepSeek

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

DeepSeek-Coder Instruct scores 70.6 on GPQA Diamond, placing it #243 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
70.6
0–100 scale
Rank
#243
of 600
Percentile
60th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
16.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with DeepSeek-Coder Instruct 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-Coder Instruct sits at #243 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 16.4 points. The median model in this index scores 68.8, which puts DeepSeek-Coder Instruct above the midpoint.

DeepSeek models average 67.5 on this benchmark. DeepSeek-Coder Instruct is 3.1 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among coding models, the average is 63.9. DeepSeek-Coder Instruct is 6.7 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 70.6 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 $4.34 per million input tokens, DeepSeek-Coder Instruct 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
Yi-Lightning 01.AI 32768 $4.22 77.2
DeepSeek-Coder Base DeepSeek 32768 $3.53 74.1
Llama 3 Baseten Baseten 128000 $3.62 74.9
Yi-Large 01.AI 32768 $3.40 73.5
DeepSeek-Coder Instruct DeepSeek 32768 $4.34 77.7
GLM-4.5 Base Zhipu AI 32768 $3.99 74.9
Llama 3 Anyscale Anyscale 65536 $3.94 74.7

Other benchmarks for DeepSeek-Coder Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.5 134 78th
SWE-bench Verified 67.2 165 73th
HumanEval 81.6 192 68th
MATH-500 81.1 189 69th
AIME 2025 73.5 196 67th
LiveCodeBench 71.7 154 74th
IFEval 84.7 197 67th
TruthfulQA 80.6 165 73th
HellaSwag 86.8 183 70th
MMMU 75.5 150 75th
Arena Elo 1392.8 237 61th

FAQ

What score does DeepSeek-Coder Instruct get on GPQA Diamond?

DeepSeek-Coder Instruct scores 70.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does DeepSeek-Coder Instruct rank on GPQA Diamond?

It ranks #243 of 600 models, in the 60th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is DeepSeek-Coder Instruct 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-Coder Instruct cost?

DeepSeek-Coder Instruct costs $4.34 per million input tokens and $20.00 per million output tokens.

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