Coding · Meta AI

Llama 3.1 on HumanEval: score, rank and what it means

Llama 3.1 scores 81.8 on HumanEval, placing it #189 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
81.8
0–100 scale
Rank
#189
of 600
Percentile
69th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
15.0
points

Score distribution

The chart shows the top 10 models on HumanEval, with Llama 3.1 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 3.1 sits at #189 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 15.0 points. The median model in this index scores 77.4, which puts Llama 3.1 above the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.1 is 8.6 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 3.1 is 0.4 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 81.8 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 $4.16 per million input tokens, Llama 3.1 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
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
Sonar Perplexity 200000 $10.57 76.0
Llama 3.1 Meta AI 200000 $4.16 76.3
o4 Mini OpenAI 200000 $11.92 77.7
ERNIE 4.0 Pro Baidu 200000 $12.58 77.5

Other benchmarks for Llama 3.1

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.8 220 63th
GPQA Diamond 69.8 272 55th
SWE-bench Verified 67.9 147 76th
MATH-500 82.8 150 75th
AIME 2025 69.5 268 55th
LiveCodeBench 66.7 258 57th
IFEval 82.3 267 56th
TruthfulQA 78.4 240 60th
HellaSwag 87.2 166 72th
MMMU 74.2 180 70th
Arena Elo 1407.6 187 69th

FAQ

What score does Llama 3.1 get on HumanEval?

Llama 3.1 scores 81.8 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.1 rank on HumanEval?

It ranks #189 of 600 models, in the 69th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.1 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 3.1 cost?

Llama 3.1 costs $4.16 per million input tokens and $15.79 per million output tokens.

Related