Coding · Meta AI

Llama 3.3 Instruct on HumanEval: score, rank and what it means

Llama 3.3 Instruct scores 82.1 on HumanEval, placing it #185 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
82.1
0–100 scale
Rank
#185
of 600
Percentile
69th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
14.7
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Llama 3.3 Instruct sits at #185 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 14.7 points. The median model in this index scores 77.4, which puts Llama 3.3 Instruct above the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.3 Instruct is 8.9 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 82.2. Llama 3.3 Instruct is 0.1 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 82.1 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 $4.33 per million input tokens, Llama 3.3 Instruct is above the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Llama 3 Novita Instruct Novita AI 32768 $3.94 75.6
Qwen3-Coder Instruct Alibaba Cloud 128000 $4.66 78.1
Hunyuan-Large Tencent 65536 $4.33 78.2
Llama 3.3 Instruct Meta AI 128000 $4.33 76.6
Sonar Max Perplexity 32768 $11.60 77.8
Reka Core Reka AI 32768 $12.17 77.4

Other benchmarks for Llama 3.3 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.7 254 58th
GPQA Diamond 70.1 257 57th
SWE-bench Verified 63.7 239 60th
MATH-500 81.9 168 72th
AIME 2025 76.9 131 78th
LiveCodeBench 67.1 247 59th
IFEval 85.4 176 71th
TruthfulQA 79.0 219 64th
HellaSwag 86.9 182 70th
MMMU 72.0 245 59th
Arena Elo 1418.0 157 74th

FAQ

What score does Llama 3.3 Instruct get on HumanEval?

Llama 3.3 Instruct scores 82.1 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.3 Instruct rank on HumanEval?

It ranks #185 of 600 models, in the 69th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.3 Instruct good at HumanEval?

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 HumanEval score calculated?

HumanEval 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 Instruct cost?

Llama 3.3 Instruct costs $4.33 per million input tokens and $19.59 per million output tokens.

Related