Preference · Meta AI

Llama 4 Maverick Chat on Arena Elo: score, rank and what it means

Llama 4 Maverick Chat scores 1419.9 on Arena Elo, placing it #150 of 600 models in the index. The benchmark average is 1349.9 and the leader is Claude Opus 4.5 Max at 1501.9.

Score
1419.9
0–100 scale
Rank
#150
of 600
Percentile
75th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
82.0
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Llama 4 Maverick Chat highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Max 1501.9
GPT-5.2 Reasoning 1500.4
GPT-5.2 Turbo 1500.3
Claude Opus 4.5 Reasoning 1497.5
GPT-5.2 Max 1495.3
Gemini 3 Pro Turbo 1494.9
Grok 4 Max 1491.4
Claude Opus 4.5 1491.2
GPT-5.1 Pro 1490.0
Grok 4 Reasoning 1487.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
2 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
3 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
6 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
7 Grok 4 Max xAI 2000000 $19.70 86.6
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
10 Grok 4 Reasoning xAI 2000000 $19.67 87.8

What this score means

On Arena Elo, Llama 4 Maverick Chat sits at #150 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 82.0 points. The median model in this index scores 1373.8, which puts Llama 4 Maverick Chat above the midpoint.

Meta AI models average 1342.5 on this benchmark. Llama 4 Maverick Chat is 77.4 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 1409.6. Llama 4 Maverick Chat is 10.3 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 1419.9 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 $5.09 per million input tokens, Llama 4 Maverick Chat is above the median input price of $4.00 across the 600 models scored on Arena Elo. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0
MiniMax-Text MiniMax 32768 $4.44 77.0
Mistral Large 3 Base Mistral AI 65536 $4.47 78.2
Gemini 3 Pro Mini Google DeepMind 128000 $12.27 78.1
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
ERNIE 4.5 Turbo Baidu 128000 $13.75 79.7
Command A Cohere 200000 $13.30 79.6

Other benchmarks for Llama 4 Maverick Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.5 169 72th
GPQA Diamond 73.0 199 67th
SWE-bench Verified 66.6 177 71th
HumanEval 83.2 157 74th
MATH-500 84.8 113 81th
AIME 2025 78.9 102 83th
LiveCodeBench 76.3 80 87th
IFEval 87.4 123 80th
TruthfulQA 81.5 142 76th
HellaSwag 88.8 119 80th
MMMU 75.4 155 74th

FAQ

What score does Llama 4 Maverick Chat get on Arena Elo?

Llama 4 Maverick Chat scores 1419.9 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Llama 4 Maverick Chat rank on Arena Elo?

It ranks #150 of 600 models, in the 75th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Llama 4 Maverick Chat good at Arena Elo?

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 Arena Elo score calculated?

Arena Elo is a preference 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 Chat cost?

Llama 4 Maverick Chat costs $5.09 per million input tokens and $23.20 per million output tokens.

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