Knowledge · Groq

Llama 3.3 Groq on MMLU-Pro: score, rank and what it means

Llama 3.3 Groq scores 78.0 on MMLU-Pro, placing it #243 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
78.0
0–100 scale
Rank
#243
of 600
Percentile
60th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
13.6
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Llama 3.3 Groq highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Llama 3.3 Groq sits at #243 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 13.6 points. The median model in this index scores 76.1, which puts Llama 3.3 Groq above the midpoint.

Groq models average 68.9 on this benchmark. Llama 3.3 Groq is 9.1 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 80.0. Llama 3.3 Groq is 2.0 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 78.0 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 $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 MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nova Lite Amazon 65536 $9.20 73.4
Mistral Small 3 Mistral AI 32768 $3.90 75.3
Hunyuan-Large Base Tencent 200000 $3.64 74.0
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Llama 3.3 Groq Groq 32768 $3.98 76.8
DeepSeek-Coder Chat DeepSeek 200000 $4.20 77.3
Llama 3.3 Chat Meta AI 32768 $4.18 76.9

Other benchmarks for Llama 3.3 Groq

BenchmarkScoreRankPercentileRelative
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
HellaSwag 86.8 186 69th
MMMU 75.2 158 74th
Arena Elo 1399.1 210 65th

FAQ

What score does Llama 3.3 Groq get on MMLU-Pro?

Llama 3.3 Groq scores 78.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Llama 3.3 Groq rank on MMLU-Pro?

It ranks #243 of 600 models, in the 60th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Llama 3.3 Groq good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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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