Coding · Meta AI

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

Llama 3.1 Chat scores 79.3 on HumanEval, placing it #256 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
79.3
0–100 scale
Rank
#256
of 600
Percentile
57th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
17.5
points

Score distribution

The chart shows the top 10 models on HumanEval, with Llama 3.1 Chat 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 Chat sits at #256 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 17.5 points. The median model in this index scores 77.4, which puts Llama 3.1 Chat above the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.1 Chat is 6.1 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 Chat is 2.9 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 79.3 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 $3.82 per million input tokens, Llama 3.1 Chat 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 3.1 Turbo Base Together AI 16384 $3.30 73.0
Phi-4 Microsoft 200000 $3.96 75.4
Yi-Large 01.AI 32768 $3.40 73.5
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Llama 3.1 Chat Meta AI 32768 $3.82 75.3
Llama 3.3 Groq Base Groq 16384 $3.24 73.5
Gemma 3 Chat Google DeepMind 65536 $3.74 74.5

Other benchmarks for Llama 3.1 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.9 186 69th
GPQA Diamond 72.4 211 65th
SWE-bench Verified 62.0 280 53th
MATH-500 78.9 239 60th
AIME 2025 67.7 300 50th
LiveCodeBench 68.5 216 64th
IFEval 81.9 280 53th
TruthfulQA 79.6 198 67th
HellaSwag 83.7 293 51th
MMMU 74.3 177 71th
Arena Elo 1392.5 239 60th

FAQ

What score does Llama 3.1 Chat get on HumanEval?

Llama 3.1 Chat scores 79.3 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.1 Chat rank on HumanEval?

It ranks #256 of 600 models, in the 57th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.1 Chat 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 Chat cost?

Llama 3.1 Chat costs $3.82 per million input tokens and $18.65 per million output tokens.

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