Commonsense · Groq

Llama 3.3 Groq on HellaSwag: score, rank and what it means

Llama 3.3 Groq scores 86.8 on HellaSwag, placing it #186 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
86.8
0–100 scale
Rank
#186
of 600
Percentile
69th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
9.3
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Llama 3.3 Groq 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, Llama 3.3 Groq sits at #186 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 9.3 points. The median model in this index scores 83.6, which puts Llama 3.3 Groq above the midpoint.

Groq models average 78.4 on this benchmark. Llama 3.3 Groq is 8.4 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 86.8. Llama 3.3 Groq is 0.0 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 86.8 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 $3.98 per million input tokens, Llama 3.3 Groq 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
Llama 3.3 Instruct Meta AI 128000 $4.33 76.6
DeepSeek-Coder Instruct DeepSeek 32768 $4.34 77.7
Llama 3 Baseten Instruct Baseten 200000 $3.91 76.2
Llama 3.1 Turbo Instruct Together AI 32768 $4.21 76.7
Llama 3.3 Groq Groq 32768 $3.98 76.8
ERNIE 4.0 Reasoning Baidu 65536 $12.20 77.8
Qwen3-Coder Alibaba Cloud 200000 $4.94 79.5

Other benchmarks for Llama 3.3 Groq

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.0 243 60th
GPQA Diamond 73.6 183 70th
SWE-bench Verified 63.9 235 61th
HumanEval 78.5 280 53th
MATH-500 78.9 240 60th
AIME 2025 74.0 181 70th
LiveCodeBench 70.4 183 70th
IFEval 85.0 192 68th
TruthfulQA 80.1 175 71th
MMMU 75.2 158 74th
Arena Elo 1399.1 210 65th

FAQ

What score does Llama 3.3 Groq get on HellaSwag?

Llama 3.3 Groq scores 86.8 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Llama 3.3 Groq rank on HellaSwag?

It ranks #186 of 600 models, in the 69th percentile. The leader is GPT-5.2 Max at 96.1.

Is Llama 3.3 Groq good at HellaSwag?

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 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 Llama 3.3 Groq cost?

Llama 3.3 Groq costs $3.98 per million input tokens and $16.20 per million output tokens.

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