Coding · Meta AI

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

Llama 3.1 Instruct scores 81.2 on HumanEval, placing it #209 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
81.2
0–100 scale
Rank
#209
of 600
Percentile
65th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
15.6
points

Score distribution

The chart shows the top 10 models on HumanEval, with Llama 3.1 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 3.1 Instruct sits at #209 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 15.6 points. The median model in this index scores 77.4, which puts Llama 3.1 Instruct above the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.1 Instruct is 8.0 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 Instruct is 1.0 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 81.2 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 $4.05 per million input tokens, Llama 3.1 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
Llama 3.1 Cerebras Instruct Cerebras 65536 $4.11 76.1
Llama 3.3 Chat Meta AI 32768 $4.18 76.9
Magistral Chat Mistral AI 128000 $4.33 76.8
Command R+ Instruct Cohere 200000 $4.16 76.2
Llama 3.1 Instruct Meta AI 200000 $4.05 75.7
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0
Llama 4 Scout Base Meta AI 32768 $3.95 75.3

Other benchmarks for Llama 3.1 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.5 196 67th
GPQA Diamond 71.8 223 63th
SWE-bench Verified 64.2 229 62th
MATH-500 77.0 278 54th
AIME 2025 72.0 220 63th
LiveCodeBench 67.0 252 58th
IFEval 85.5 174 71th
TruthfulQA 79.0 217 64th
HellaSwag 84.9 252 58th
MMMU 70.9 274 54th
Arena Elo 1395.5 226 62th

FAQ

What score does Llama 3.1 Instruct get on HumanEval?

Llama 3.1 Instruct scores 81.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.1 Instruct rank on HumanEval?

It ranks #209 of 600 models, in the 65th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.1 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 3.1 Instruct cost?

Llama 3.1 Instruct costs $4.05 per million input tokens and $16.24 per million output tokens.

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