Instruction following · Meta AI

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

Llama 3.3 Chat scores 85.0 on IFEval, placing it #191 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
#191
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 Chat 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 Chat sits at #191 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 Chat above the midpoint.

Meta AI models average 77.8 on this benchmark. Llama 3.3 Chat is 7.2 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 85.2. Llama 3.3 Chat 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 $4.18 per million input tokens, Llama 3.3 Chat is above 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
Reka Flash Reasoning Reka AI 32768 $10.70 75.6
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

Other benchmarks for Llama 3.3 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.9 245 59th
GPQA Diamond 74.4 157 74th
SWE-bench Verified 67.7 154 74th
HumanEval 81.3 206 66th
MATH-500 79.5 222 63th
AIME 2025 70.4 252 58th
LiveCodeBench 69.7 197 67th
TruthfulQA 79.0 218 64th
HellaSwag 87.1 173 71th
MMMU 73.4 207 66th
Arena Elo 1399.7 208 65th

FAQ

What score does Llama 3.3 Chat get on IFEval?

Llama 3.3 Chat 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 Chat rank on IFEval?

It ranks #191 of 600 models, in the 68th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Llama 3.3 Chat 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 Chat cost?

Llama 3.3 Chat costs $4.18 per million input tokens and $17.67 per million output tokens.

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