Coding · Meta AI

Llama 3.1 7B on HumanEval: score, rank and what it means

Llama 3.1 7B scores 60.4 on HumanEval, placing it #498 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
60.4
0–100 scale
Rank
#498
of 600
Percentile
17th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
36.4
points

Score distribution

The chart shows the top 10 models on HumanEval, with Llama 3.1 7B 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 7B sits at #498 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 36.4 points. The median model in this index scores 77.4, which puts Llama 3.1 7B below the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.1 7B is 12.8 points below that provider line, so it is a weaker result than the average Meta AI model.

Among small open-weight models, the average is 56.7. Llama 3.1 7B is 3.7 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 60.4 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 $1.01 per million input tokens, Llama 3.1 7B is below 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 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
Llama 3.1 Cerebras 8B Cerebras 32768 $1.02 58.2
Mistral Small 3 7B Mistral AI 4096 $0.89 55.2
Embed 4 Mini Cohere 4096 $2.48 55.8
Llama 3.1 7B Meta AI 8192 $1.01 57.4
Yi-Lightning 8B 01.AI 4096 $1.16 59.2
Llama 3.1 Cerebras 7B Cerebras 32768 $0.95 56.5

Other benchmarks for Llama 3.1 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 64.8 456 24th
GPQA Diamond 54.4 474 21th
SWE-bench Verified 44.1 477 21th
MATH-500 58.8 481 20th
AIME 2025 46.9 480 20th
LiveCodeBench 45.0 499 17th
IFEval 67.5 494 18th
TruthfulQA 63.8 473 21th
HellaSwag 71.1 518 14th
MMMU 54.5 503 16th
Arena Elo 1237.4 518 14th

FAQ

What score does Llama 3.1 7B get on HumanEval?

Llama 3.1 7B scores 60.4 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.1 7B rank on HumanEval?

It ranks #498 of 600 models, in the 17th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.1 7B good at HumanEval?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 7B cost?

Llama 3.1 7B costs $1.01 per million input tokens and $3.79 per million output tokens.

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