Mathematics · Hyperbolic

Llama 3 Hyperbolic Instruct on MATH-500: score, rank and what it means

Llama 3 Hyperbolic Instruct scores 81.2 on MATH-500, placing it #186 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
81.2
0–100 scale
Rank
#186
of 600
Percentile
69th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
15.5
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 3 Hyperbolic Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Llama 3 Hyperbolic Instruct sits at #186 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 15.5 points. The median model in this index scores 76.0, which puts Llama 3 Hyperbolic Instruct above the midpoint.

Hyperbolic models average 67.8 on this benchmark. Llama 3 Hyperbolic Instruct is 13.4 points above that provider line, so it is a stronger result than the average Hyperbolic model.

Among multimodal models, the average is 81.3. Llama 3 Hyperbolic Instruct is 0.1 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 81.2 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 $3.79 per million input tokens, Llama 3 Hyperbolic Instruct is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemini 3 Pro Mini Google DeepMind 128000 $12.27 78.1
Llama 3 Modal Instruct Modal 128000 $3.84 75.2
Yi-Lightning Chat 01.AI 32768 $3.79 75.5
GPT-5.2 Mini OpenAI 200000 $13.34 80.4
Llama 3 Hyperbolic Instruct Hyperbolic 200000 $3.79 76.2
Seed-OSS Instruct ByteDance 128000 $3.79 76.0
o3 Mini OpenAI 128000 $10.68 76.2

Other benchmarks for Llama 3 Hyperbolic Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.9 212 65th
GPQA Diamond 70.1 256 57th
SWE-bench Verified 66.2 189 69th
HumanEval 79.4 251 58th
AIME 2025 70.4 251 58th
LiveCodeBench 69.0 208 65th
IFEval 83.6 223 63th
TruthfulQA 79.4 203 66th
HellaSwag 85.9 219 64th
MMMU 74.1 185 69th
Arena Elo 1385.7 264 56th

FAQ

What score does Llama 3 Hyperbolic Instruct get on MATH-500?

Llama 3 Hyperbolic Instruct scores 81.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 3 Hyperbolic Instruct rank on MATH-500?

It ranks #186 of 600 models, in the 69th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 3 Hyperbolic Instruct good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 Instruct cost?

Llama 3 Hyperbolic Instruct costs $3.79 per million input tokens and $16.16 per million output tokens.

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