Multimodal · DeepSeek

DeepSeek-R1 Instruct on MMMU: score, rank and what it means

DeepSeek-R1 Instruct scores 81.5 on MMMU, placing it #37 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
81.5
0–100 scale
Rank
#37
of 600
Percentile
94th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
5.4
points

Score distribution

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

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, DeepSeek-R1 Instruct sits at #37 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 5.4 points. The median model in this index scores 70.0, which puts DeepSeek-R1 Instruct above the midpoint.

DeepSeek models average 68.9 on this benchmark. DeepSeek-R1 Instruct is 12.6 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among frontier models, the average is 81.6. DeepSeek-R1 Instruct is 0.1 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 81.5 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 $5.90 per million input tokens, DeepSeek-R1 Instruct is above the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
o4 Max OpenAI 2000000 $19.51 86.2
o4 Reasoning OpenAI 1000000 $19.69 87.5
Grok 4 Turbo xAI 1000000 $19.21 86.7
GPT-5.1 Pro OpenAI 200000 $19.77 87.8
DeepSeek-R1 Instruct DeepSeek 1000000 $5.90 83.1
GPT-4.1 Pro OpenAI 400000 $17.56 85.2
GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5

Other benchmarks for DeepSeek-R1 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.9 63 90th
GPQA Diamond 81.4 37 94th
SWE-bench Verified 72.4 69 89th
HumanEval 88.0 72 88th
MATH-500 86.2 88 85th
AIME 2025 77.6 120 80th
LiveCodeBench 79.6 49 92th
IFEval 88.9 83 86th
TruthfulQA 82.2 127 79th
HellaSwag 91.1 59 90th
Arena Elo 1447.7 80 87th

FAQ

What score does DeepSeek-R1 Instruct get on MMMU?

DeepSeek-R1 Instruct scores 81.5 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does DeepSeek-R1 Instruct rank on MMMU?

It ranks #37 of 600 models, in the 94th percentile. The leader is GPT-5.2 Max at 86.9.

Is DeepSeek-R1 Instruct good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 Instruct cost?

DeepSeek-R1 Instruct costs $5.90 per million input tokens and $26.49 per million output tokens.

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