Coding · Groq

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

Llama 3.3 Groq scores 70.4 on LiveCodeBench, placing it #183 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
70.4
0–100 scale
Rank
#183
of 600
Percentile
70th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
14.7
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Llama 3.3 Groq sits at #183 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 14.7 points. The median model in this index scores 64.7, which puts Llama 3.3 Groq above the midpoint.

Groq models average 55.6 on this benchmark. Llama 3.3 Groq is 14.8 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 70.3. Llama 3.3 Groq is 0.1 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 70.4 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.5 Turbo Baidu 128000 $13.75 79.7
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5
Llama 3 Lambda Instruct Lambda 32768 $3.92 75.8
Reka Core Max Reka AI 128000 $13.41 79.3
Llama 3.3 Groq Groq 32768 $3.98 76.8
MiniMax-M2 Chat MiniMax 200000 $5.02 80.2
Llama 3 Replicate Chat Replicate 200000 $3.74 74.7

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
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 LiveCodeBench?

Llama 3.3 Groq scores 70.4 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3.3 Groq rank on LiveCodeBench?

It ranks #183 of 600 models, in the 70th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3.3 Groq good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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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