Mathematics · Cerebras

Llama 3.1 Cerebras on MATH-500: score, rank and what it means

Llama 3.1 Cerebras scores 82.4 on MATH-500, placing it #155 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
82.4
0–100 scale
Rank
#155
of 600
Percentile
74th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
14.3
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 3.1 Cerebras 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 3.1 Cerebras sits at #155 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 14.3 points. The median model in this index scores 76.0, which puts Llama 3.1 Cerebras above the midpoint.

Cerebras models average 68.5 on this benchmark. Llama 3.1 Cerebras is 13.9 points above that provider line, so it is a stronger result than the average Cerebras model.

Among multimodal models, the average is 81.3. Llama 3.1 Cerebras is 1.1 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 82.4 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 $4.01 per million input tokens, Llama 3.1 Cerebras is above 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
Llama 4 Maverick Meta AI 200000 $5.36 81.6
Kimi K1.5 Instruct Moonshot AI 200000 $5.15 80.5
Qwen3-Max Mini Alibaba Cloud 128000 $11.13 76.5
ERNIE 4.5 Reasoning Baidu 1000000 $14.36 79.8
Llama 3.1 Cerebras Cerebras 128000 $4.01 76.0
Qwen3-Coder Base Alibaba Cloud 200000 $3.99 76.6
MiniMax-M2 MiniMax 200000 $5.19 80.6

Other benchmarks for Llama 3.1 Cerebras

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.4 295 51th
GPQA Diamond 74.4 156 74th
SWE-bench Verified 64.9 214 64th
HumanEval 81.3 204 66th
AIME 2025 69.8 260 57th
LiveCodeBench 66.1 273 55th
IFEval 84.6 199 67th
TruthfulQA 80.6 166 72th
HellaSwag 85.1 239 60th
MMMU 70.1 298 50th
Arena Elo 1411.3 179 70th

FAQ

What score does Llama 3.1 Cerebras get on MATH-500?

Llama 3.1 Cerebras scores 82.4 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 3.1 Cerebras rank on MATH-500?

It ranks #155 of 600 models, in the 74th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 3.1 Cerebras 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 3.1 Cerebras cost?

Llama 3.1 Cerebras costs $4.01 per million input tokens and $15.13 per million output tokens.

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