Coding · Meta AI

Llama 4 Maverick Base on SWE-bench Verified: score, rank and what it means

Llama 4 Maverick Base scores 67.9 on SWE-bench Verified, placing it #148 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
67.9
0–100 scale
Rank
#148
of 600
Percentile
75th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
13.8
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Llama 4 Maverick Base highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Llama 4 Maverick Base sits at #148 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 13.8 points. The median model in this index scores 61.0, which puts Llama 4 Maverick Base above the midpoint.

Meta AI models average 56.9 on this benchmark. Llama 4 Maverick Base is 11.0 points above that provider line, so it is a stronger result than the average Meta AI model.

Among multimodal models, the average is 66.4. Llama 4 Maverick Base is 1.5 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 67.9 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 $4.68 per million input tokens, Llama 4 Maverick Base is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Sonnet 4.5 Mini Anthropic 32768 $11.43 76.5
ERNIE 4.0 Max Baidu 32768 $12.40 78.9
Gemini 3 Pro Mini Google DeepMind 128000 $12.27 78.1
Llama 3.1 Meta AI 200000 $4.16 76.3
Llama 4 Maverick Base Meta AI 128000 $4.68 79.1
Hunyuan-Large Tencent 65536 $4.33 78.2
Hunyuan-Turbo Turbo Tencent 65536 $11.60 77.4

Other benchmarks for Llama 4 Maverick Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.3 100 83th
GPQA Diamond 71.8 224 63th
HumanEval 85.4 107 82th
MATH-500 83.3 142 76th
AIME 2025 77.8 117 81th
LiveCodeBench 69.3 203 66th
IFEval 87.4 122 80th
TruthfulQA 81.2 150 75th
HellaSwag 89.2 109 82th
MMMU 73.8 197 67th
Arena Elo 1425.2 129 79th

FAQ

What score does Llama 4 Maverick Base get on SWE-bench Verified?

Llama 4 Maverick Base scores 67.9 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Llama 4 Maverick Base rank on SWE-bench Verified?

It ranks #148 of 600 models, in the 75th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Llama 4 Maverick Base good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified is a coding 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 Base cost?

Llama 4 Maverick Base costs $4.68 per million input tokens and $21.03 per million output tokens.

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