Instruction following · Groq

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

Llama 3.3 Groq scores 85.0 on IFEval, placing it #192 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
85.0
0–100 scale
Rank
#192
of 600
Percentile
68th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
11.1
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, Llama 3.3 Groq sits at #192 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 11.1 points. The median model in this index scores 81.2, which puts Llama 3.3 Groq above the midpoint.

Groq models average 74.3 on this benchmark. Llama 3.3 Groq is 10.7 points above that provider line, so it is a stronger result than the average Groq model.

Among multimodal models, the average is 85.2. Llama 3.3 Groq is 0.2 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 85.0 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 IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Max Perplexity 32768 $11.60 77.8
Sonar Reasoning Perplexity 200000 $11.48 76.2
Command R+ Cohere 32768 $3.96 76.3
Llama 3.3 Chat Meta AI 32768 $4.18 76.9
Llama 3.3 Groq Groq 32768 $3.98 76.8
Qwen3-Coder Chat Alibaba Cloud 128000 $4.59 78.4
Hunyuan-Turbo Tencent 128000 $10.55 75.8

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
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 IFEval?

Llama 3.3 Groq scores 85.0 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Llama 3.3 Groq rank on IFEval?

It ranks #192 of 600 models, in the 68th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Llama 3.3 Groq good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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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