Mathematics · Meta AI

Llama 4 Scout 8B on MATH-500: score, rank and what it means

Llama 4 Scout 8B scores 62.7 on MATH-500, placing it #439 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
62.7
0–100 scale
Rank
#439
of 600
Percentile
27th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
34.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Llama 4 Scout 8B 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 8B sits at #439 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 34.0 points. The median model in this index scores 76.0, which puts Llama 4 Scout 8B below the midpoint.

Meta AI models average 71.4 on this benchmark. Llama 4 Scout 8B is 8.7 points below that provider line, so it is a weaker result than the average Meta AI model.

Among small open-weight models, the average is 53.7. Llama 4 Scout 8B is 9.0 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 62.7 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 $1.46 per million input tokens, Llama 4 Scout 8B 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
Firefunction Mini Fireworks AI 32768 $4.63 63.2
GPT-NeoX Chat EleutherAI 16384 $1.49 60.1
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9
Llama 4 Scout 8B Meta AI 8192 $1.46 61.2
Zephyr Base Hugging Face 4096 $1.26 59.5
MiniMax-M2 8B MiniMax 32768 $1.65 61.7

Other benchmarks for Llama 4 Scout 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.5 425 29th
GPQA Diamond 58.9 418 30th
SWE-bench Verified 48.1 436 27th
HumanEval 66.3 426 29th
AIME 2025 50.2 458 24th
LiveCodeBench 49.7 452 25th
IFEval 71.8 430 28th
TruthfulQA 65.8 446 26th
HellaSwag 73.7 462 23th
MMMU 58.1 457 24th
Arena Elo 1266.8 466 22th

FAQ

What score does Llama 4 Scout 8B get on MATH-500?

Llama 4 Scout 8B scores 62.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Llama 4 Scout 8B rank on MATH-500?

It ranks #439 of 600 models, in the 27th percentile. The leader is GPT-5.2 Max at 96.7.

Is Llama 4 Scout 8B good at MATH-500?

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 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 8B cost?

Llama 4 Scout 8B costs $1.46 per million input tokens and $6.51 per million output tokens.

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