Commonsense · Hugging Face

Zephyr Instruct on HellaSwag: score, rank and what it means

Zephyr Instruct scores 75.7 on HellaSwag, placing it #431 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
75.7
0–100 scale
Rank
#431
of 600
Percentile
28th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
20.4
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Zephyr Instruct 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, Zephyr Instruct sits at #431 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 20.4 points. The median model in this index scores 83.6, which puts Zephyr Instruct below the midpoint.

Hugging Face models average 70.2 on this benchmark. Zephyr Instruct is 5.5 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 80.2. Zephyr Instruct is 4.5 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 75.7 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 $1.66 per million input tokens, Zephyr Instruct 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
SmolLM3 Chat Hugging Face 16384 $1.61 62.1
DeepSeek-V3.2 7B DeepSeek 4096 $1.75 63.2
Firefunction Mini Fireworks AI 32768 $4.63 63.2
Llama 3.3 8B Meta AI 8192 $1.26 60.1
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Mistral Large 3 7B Mistral AI 32768 $1.44 61.1
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9

Other benchmarks for Zephyr Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.8 440 27th
GPQA Diamond 59.3 412 31th
SWE-bench Verified 51.3 412 31th
HumanEval 65.1 441 27th
MATH-500 62.9 437 27th
AIME 2025 56.9 405 33th
LiveCodeBench 50.0 449 25th
IFEval 71.8 433 28th
TruthfulQA 66.4 440 27th
MMMU 60.9 422 30th
Arena Elo 1301.5 416 31th

FAQ

What score does Zephyr Instruct get on HellaSwag?

Zephyr Instruct scores 75.7 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Zephyr Instruct rank on HellaSwag?

It ranks #431 of 600 models, in the 28th percentile. The leader is GPT-5.2 Max at 96.1.

Is Zephyr Instruct 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 Zephyr Instruct cost?

Zephyr Instruct costs $1.66 per million input tokens and $6.50 per million output tokens.

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