Instruction following · DeepSeek

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

DeepSeek-R1 scores 91.0 on IFEval, placing it #53 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
91.0
0–100 scale
Rank
#53
of 600
Percentile
91th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
5.1
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, DeepSeek-R1 sits at #53 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 5.1 points. The median model in this index scores 81.2, which puts DeepSeek-R1 above the midpoint.

DeepSeek models average 80.3 on this benchmark. DeepSeek-R1 is 10.7 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among multimodal models, the average is 85.2. DeepSeek-R1 is 5.8 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 91.0 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 $5.83 per million input tokens, DeepSeek-R1 is above the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Grok 4 Pro xAI 1000000 $19.00 85.4
Claude Sonnet 4.5 Anthropic 400000 $17.84 86.0
Grok 4 Turbo xAI 1000000 $19.21 86.7
o4 Max OpenAI 2000000 $19.51 86.2
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
Gemini 3 Flash Google DeepMind 128000 $15.67 83.6
Grok 3 xAI 128000 $15.84 82.8

Other benchmarks for DeepSeek-R1

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.8 85 86th
GPQA Diamond 77.8 89 85th
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
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 IFEval?

DeepSeek-R1 scores 91.0 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does DeepSeek-R1 rank on IFEval?

It ranks #53 of 600 models, in the 91st percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is DeepSeek-R1 good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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.

Related