Coding · Meta AI

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

Llama 3.3 Base scores 77.7 on HumanEval, placing it #294 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
77.7
0–100 scale
Rank
#294
of 600
Percentile
51th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
19.1
points

Score distribution

The chart shows the top 10 models on HumanEval, with Llama 3.3 Base 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 Base sits at #294 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 19.1 points. The median model in this index scores 77.4, which puts Llama 3.3 Base above the midpoint.

Meta AI models average 73.2 on this benchmark. Llama 3.3 Base is 4.5 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 Base is 4.5 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 77.7 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 $3.63 per million input tokens, Llama 3.3 Base 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
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
Llama 3 Novita Chat Novita AI 65536 $3.50 74.2
Phi-4 Instruct Microsoft 128000 $3.79 75.3
Gemini 3 Pro Nano Google DeepMind 8192 $9.11 73.2
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Mixtral Turbo Together AI 65536 $3.20 72.4
Reka Flash Turbo Reka AI 128000 $10.19 75.1

Other benchmarks for Llama 3.3 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.7 190 68th
GPQA Diamond 71.4 233 61th
SWE-bench Verified 62.5 267 56th
MATH-500 77.0 279 54th
AIME 2025 71.5 227 62th
LiveCodeBench 64.8 297 51th
IFEval 80.4 323 46th
TruthfulQA 76.5 294 51th
HellaSwag 83.0 320 47th
MMMU 69.7 312 48th
Arena Elo 1396.4 220 63th

FAQ

What score does Llama 3.3 Base get on HumanEval?

Llama 3.3 Base scores 77.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Llama 3.3 Base rank on HumanEval?

It ranks #294 of 600 models, in the 51st percentile. The leader is GPT-5.2 Pro at 96.8.

Is Llama 3.3 Base 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 Base cost?

Llama 3.3 Base costs $3.63 per million input tokens and $15.34 per million output tokens.

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