Mathematics · Groq

Llama 3.3 Groq on MATH-500: score, rank and what it means

Llama 3.3 Groq scores 78.9 on MATH-500, placing it #240 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
78.9
0–100 scale
Rank
#240
of 600
Percentile
60th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
17.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 3.3 Groq highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Llama 3.3 Groq sits at #240 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 17.8 points. The median model in this index scores 76.0, which puts Llama 3.3 Groq above the midpoint.

Groq models average 66.1 on this benchmark. Llama 3.3 Groq is 12.8 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 81.3. Llama 3.3 Groq is 2.4 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 78.9 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Phi-4 Microsoft 200000 $3.96 75.4
Gemini 3 Flash Mini Google DeepMind 200000 $10.71 76.0
Gemma 3 Instruct Google DeepMind 128000 $3.72 74.1
Llama 3.1 Chat Meta AI 32768 $3.82 75.3
Llama 3.3 Groq Groq 32768 $3.98 76.8
Llama 3 Anyscale Anyscale 65536 $3.94 74.7
Nova Lite Pro Amazon 200000 $9.69 74.1

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
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 MATH-500?

Llama 3.3 Groq scores 78.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 3.3 Groq rank on MATH-500?

It ranks #240 of 600 models, in the 60th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 3.3 Groq good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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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