Knowledge · Groq

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

Llama 3.3 Groq Base scores 75.3 on MMLU-Pro, placing it #324 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
75.3
0–100 scale
Rank
#324
of 600
Percentile
46th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
16.3
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Llama 3.3 Groq Base 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 Base sits at #324 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 16.3 points. The median model in this index scores 76.1, which puts Llama 3.3 Groq Base below the midpoint.

Groq models average 68.9 on this benchmark. Llama 3.3 Groq Base is 6.4 points above that provider line, so it is a stronger result than the average Groq model.

Among open-weight models, the average is 72.1. Llama 3.3 Groq Base is 3.2 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 75.3 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 $3.24 per million input tokens, Llama 3.3 Groq Base 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
GPT-5.2 Nano OpenAI 128000 $9.73 73.5
Gemma 3 Instruct Google DeepMind 128000 $3.72 74.1
Yi-Large Base 01.AI 16384 $2.78 70.3
Firefunction Max Fireworks AI 32768 $9.12 73.2
Llama 3.3 Groq Base Groq 16384 $3.24 73.5
o3 Nano OpenAI 32768 $7.78 70.6
DBRX Chat Databricks 65536 $3.07 71.7

Other benchmarks for Llama 3.3 Groq Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 65.6 351 42th
SWE-bench Verified 61.0 298 50th
HumanEval 79.3 257 57th
MATH-500 77.3 271 55th
AIME 2025 71.0 235 61th
LiveCodeBench 66.8 257 57th
IFEval 81.0 310 48th
TruthfulQA 75.9 310 48th
HellaSwag 85.2 235 61th
MMMU 69.8 311 48th
Arena Elo 1375.9 288 52th

FAQ

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

Llama 3.3 Groq Base scores 75.3 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 Base rank on MMLU-Pro?

It ranks #324 of 600 models, in the 46th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Llama 3.3 Groq Base good at MMLU-Pro?

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 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 Base cost?

Llama 3.3 Groq Base costs $3.24 per million input tokens and $12.28 per million output tokens.

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