Commonsense · DeepSeek

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

DeepSeek-R1 7B scores 77.3 on HellaSwag, placing it #411 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
77.3
0–100 scale
Rank
#411
of 600
Percentile
32th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
18.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with DeepSeek-R1 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, DeepSeek-R1 7B sits at #411 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 18.8 points. The median model in this index scores 83.6, which puts DeepSeek-R1 7B below the midpoint.

DeepSeek models average 82.7 on this benchmark. DeepSeek-R1 7B is 5.4 points below that provider line, so it is a weaker result than the average DeepSeek model.

Among small open-weight models, the average is 70.2. DeepSeek-R1 7B is 7.1 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 77.3 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Fusion Mini OpenRouter 4096 $4.89 63.3
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
DeepSeek-R1 7B DeepSeek 32768 $1.79 63.0
Firesearch Mini Fireworks AI 32768 $3.94 61.5
StableLM 2 Stability AI 8192 $1.91 65.0

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
IFEval 71.7 434 28th
TruthfulQA 67.5 423 30th
MMMU 61.8 410 32th
Arena Elo 1297.5 424 29th

FAQ

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

DeepSeek-R1 7B scores 77.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does DeepSeek-R1 7B rank on HellaSwag?

It ranks #411 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Max at 96.1.

Is DeepSeek-R1 7B good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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