Mathematics · Meta AI

Llama 4 Scout on MATH-500: score, rank and what it means

Llama 4 Scout scores 81.0 on MATH-500, placing it #192 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
81.0
0–100 scale
Rank
#192
of 600
Percentile
68th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
15.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 4 Scout 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 4 Scout sits at #192 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 15.7 points. The median model in this index scores 76.0, which puts Llama 4 Scout above the midpoint.

Meta AI models average 71.4 on this benchmark. Llama 4 Scout is 9.6 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 81.3. Llama 4 Scout is 0.3 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 81.0 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 $4.90 per million input tokens, Llama 4 Scout 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
o3 Mini OpenAI 128000 $10.68 76.2
DeepSeek-Coder Instruct DeepSeek 32768 $4.34 77.7
Nova Pro Turbo Amazon 128000 $13.18 78.4
Reka Core Turbo Reka AI 32768 $12.58 78.4
Llama 4 Scout Meta AI 200000 $4.90 79.3
Llama 3.1 Cerebras Instruct Cerebras 65536 $4.11 76.1
Kimi K2 Base Moonshot AI 65536 $4.82 79.2

Other benchmarks for Llama 4 Scout

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.9 123 80th
GPQA Diamond 74.1 165 73th
SWE-bench Verified 70.4 103 83th
HumanEval 86.5 96 84th
AIME 2025 74.2 173 71th
LiveCodeBench 72.1 145 76th
IFEval 86.9 136 77th
TruthfulQA 82.1 128 79th
HellaSwag 88.9 114 81th
MMMU 74.1 188 69th
Arena Elo 1431.8 119 80th

FAQ

What score does Llama 4 Scout get on MATH-500?

Llama 4 Scout scores 81.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 4 Scout rank on MATH-500?

It ranks #192 of 600 models, in the 68th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 4 Scout 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 4 Scout cost?

Llama 4 Scout costs $4.90 per million input tokens and $24.91 per million output tokens.

Related