Reasoning · Meta AI

Llama 4 Maverick Instruct on GPQA Diamond: score, rank and what it means

Llama 4 Maverick Instruct scores 79.5 on GPQA Diamond, placing it #67 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
79.5
0–100 scale
Rank
#67
of 600
Percentile
89th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
7.5
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Llama 4 Maverick Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Llama 4 Maverick Instruct sits at #67 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 7.5 points. The median model in this index scores 68.8, which puts Llama 4 Maverick Instruct above the midpoint.

Meta AI models average 64.6 on this benchmark. Llama 4 Maverick Instruct is 14.9 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 73.5. Llama 4 Maverick Instruct is 6.0 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 79.5 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 $5.33 per million input tokens, Llama 4 Maverick Instruct is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-V3.2 DeepSeek 1000000 $5.88 84.0
Claude Sonnet 4.5 Vision Anthropic 128000 $16.99 83.8
Mistral Large 3 Mistral AI 128000 $5.41 81.7
o3 Reasoning OpenAI 200000 $18.07 85.3
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Grok 4 Pro xAI 1000000 $19.00 85.4

Other benchmarks for Llama 4 Maverick Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.6 70 88th
SWE-bench Verified 69.1 130 78th
HumanEval 85.0 117 81th
MATH-500 83.4 139 77th
AIME 2025 79.9 91 85th
LiveCodeBench 75.8 84 86th
IFEval 88.9 86 86th
TruthfulQA 84.0 84 86th
HellaSwag 89.6 98 84th
MMMU 79.0 73 88th
Arena Elo 1438.5 100 83th

FAQ

What score does Llama 4 Maverick Instruct get on GPQA Diamond?

Llama 4 Maverick Instruct scores 79.5 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Llama 4 Maverick Instruct rank on GPQA Diamond?

It ranks #67 of 600 models, in the 89th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Llama 4 Maverick Instruct good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Maverick Instruct cost?

Llama 4 Maverick Instruct costs $5.33 per million input tokens and $23.04 per million output tokens.

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