Commonsense · Meta AI

Llama 3.1 Base on HellaSwag: score, rank and what it means

Llama 3.1 Base scores 81.9 on HellaSwag, placing it #351 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
81.9
0–100 scale
Rank
#351
of 600
Percentile
42th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
14.2
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Llama 3.1 Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Llama 3.1 Base sits at #351 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 14.2 points. The median model in this index scores 83.6, which puts Llama 3.1 Base below the midpoint.

Meta AI models average 80.6 on this benchmark. Llama 3.1 Base is 1.3 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 86.8. Llama 3.1 Base is 4.9 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 81.9 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 $3.39 per million input tokens, Llama 3.1 Base is below the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Replicate Base Replicate 65536 $3.15 72.1
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Firefunction Turbo Fireworks AI 32768 $8.44 70.7
Gemini 3 Pro Nano Google DeepMind 8192 $9.11 73.2
Llama 3.1 Base Meta AI 32768 $3.39 72.2
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7
Yi-Lightning Base 01.AI 16384 $3.31 72.7

Other benchmarks for Llama 3.1 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.2 328 45th
GPQA Diamond 68.3 308 49th
SWE-bench Verified 59.9 329 45th
HumanEval 76.4 322 46th
MATH-500 77.0 277 54th
AIME 2025 64.7 341 43th
LiveCodeBench 61.7 353 41th
IFEval 83.0 242 60th
TruthfulQA 75.7 315 48th
MMMU 69.9 308 49th
Arena Elo 1369.7 318 47th

FAQ

What score does Llama 3.1 Base get on HellaSwag?

Llama 3.1 Base scores 81.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Llama 3.1 Base rank on HellaSwag?

It ranks #351 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Max at 96.1.

Is Llama 3.1 Base good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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 Base cost?

Llama 3.1 Base costs $3.39 per million input tokens and $16.57 per million output tokens.

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