Commonsense · Hyperbolic

Llama 3 Hyperbolic Base on HellaSwag: score, rank and what it means

Llama 3 Hyperbolic Base scores 83.3 on HellaSwag, placing it #313 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
83.3
0–100 scale
Rank
#313
of 600
Percentile
48th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
12.8
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Llama 3 Hyperbolic 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 Hyperbolic Base sits at #313 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 12.8 points. The median model in this index scores 83.6, which puts Llama 3 Hyperbolic Base below the midpoint.

Hyperbolic models average 78.2 on this benchmark. Llama 3 Hyperbolic Base is 5.1 points above that provider line, so it is a stronger result than the average Hyperbolic model.

Among open-weight models, the average is 80.2. Llama 3 Hyperbolic Base is 3.1 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 83.3 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 $3.02 per million input tokens, Llama 3 Hyperbolic 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
Mistral Small 3 Base Mistral AI 16384 $3.19 72.7
Phi-4 Instruct Microsoft 128000 $3.79 75.3
Codestral Base Mistral AI 8192 $3.31 73.1
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
DBRX Instruct Databricks 8192 $3.21 72.4

Other benchmarks for Llama 3 Hyperbolic Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 73.3 366 39th
GPQA Diamond 64.3 375 38th
SWE-bench Verified 58.2 353 41th
HumanEval 74.3 354 41th
MATH-500 77.1 275 54th
AIME 2025 69.3 272 55th
LiveCodeBench 62.5 341 43th
IFEval 79.0 355 41th
TruthfulQA 72.5 375 38th
MMMU 68.6 332 45th
Arena Elo 1369.8 317 47th

FAQ

What score does Llama 3 Hyperbolic Base get on HellaSwag?

Llama 3 Hyperbolic Base scores 83.3 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Llama 3 Hyperbolic Base rank on HellaSwag?

It ranks #313 of 600 models, in the 48th percentile. The leader is GPT-5.2 Max at 96.1.

Is Llama 3 Hyperbolic 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 Hyperbolic Base cost?

Llama 3 Hyperbolic Base costs $3.02 per million input tokens and $10.87 per million output tokens.

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