Instruction following · DeepSeek

DeepSeek-R1 7B on IFEval: score, rank and what it means

DeepSeek-R1 7B scores 71.7 on IFEval, placing it #434 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
71.7
0–100 scale
Rank
#434
of 600
Percentile
28th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
24.4
points

Score distribution

The chart shows the top 10 models on IFEval, with DeepSeek-R1 7B 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 7B sits at #434 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 24.4 points. The median model in this index scores 81.2, which puts DeepSeek-R1 7B below the midpoint.

DeepSeek models average 80.3 on this benchmark. DeepSeek-R1 7B is 8.6 points below that provider line, so it is a weaker result than the average DeepSeek model.

Among small open-weight models, the average is 64.9. DeepSeek-R1 7B is 6.8 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 71.7 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 $1.79 per million input tokens, DeepSeek-R1 7B is below 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
Llama 4 Scout 8B Meta AI 8192 $1.46 61.2
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Zephyr Chat Hugging Face 4096 $1.49 61.3
Zephyr Instruct Hugging Face 4096 $1.66 62.4
DeepSeek-R1 7B DeepSeek 32768 $1.79 63.0
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
QwQ 8B Alibaba Cloud 16384 $1.37 59.5

Other benchmarks for DeepSeek-R1 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.4 402 33th
GPQA Diamond 57.7 431 28th
SWE-bench Verified 53.1 397 34th
HumanEval 65.3 437 27th
MATH-500 64.0 424 29th
AIME 2025 53.0 434 28th
LiveCodeBench 52.2 425 29th
TruthfulQA 67.5 423 30th
HellaSwag 77.3 411 32th
MMMU 61.8 410 32th
Arena Elo 1297.5 424 29th

FAQ

What score does DeepSeek-R1 7B get on IFEval?

DeepSeek-R1 7B scores 71.7 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does DeepSeek-R1 7B rank on IFEval?

It ranks #434 of 600 models, in the 28th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is DeepSeek-R1 7B good at IFEval?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 7B cost?

DeepSeek-R1 7B costs $1.79 per million input tokens and $9.81 per million output tokens.

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