Coding · Meta AI

Llama 4 Maverick 8B on SWE-bench Verified: score, rank and what it means

Llama 4 Maverick 8B scores 52.1 on SWE-bench Verified, placing it #404 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
52.1
0–100 scale
Rank
#404
of 600
Percentile
33th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
29.6
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Llama 4 Maverick 8B 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 8B sits at #404 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 29.6 points. The median model in this index scores 61.0, which puts Llama 4 Maverick 8B below the midpoint.

Meta AI models average 56.9 on this benchmark. Llama 4 Maverick 8B is 4.8 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 39.0. Llama 4 Maverick 8B is 13.1 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 52.1 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 $1.64 per million input tokens, Llama 4 Maverick 8B is below 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
Nova Lite Mini Amazon 16384 $5.43 65.0
Kimi K2 7B Moonshot AI 16384 $1.72 62.7
Firefunction Mini Fireworks AI 32768 $4.63 63.2
Hunyuan-Turbo Mini Tencent 8192 $6.59 68.3
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4
Embed 4 Pro Cohere 4096 $5.05 63.5
OLMo 2 Base Allen Institute for AI 65536 $2.39 67.4

Other benchmarks for Llama 4 Maverick 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.6 400 33th
GPQA Diamond 57.2 436 27th
HumanEval 67.5 417 31th
MATH-500 64.2 423 30th
AIME 2025 54.3 421 30th
LiveCodeBench 51.2 437 27th
IFEval 72.6 423 30th
TruthfulQA 69.8 403 33th
HellaSwag 76.7 418 30th
MMMU 62.6 403 33th
Arena Elo 1281.1 441 27th

FAQ

What score does Llama 4 Maverick 8B get on SWE-bench Verified?

Llama 4 Maverick 8B scores 52.1 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 8B rank on SWE-bench Verified?

It ranks #404 of 600 models, in the 33rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is Llama 4 Maverick 8B good at SWE-bench Verified?

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 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 8B cost?

Llama 4 Maverick 8B costs $1.64 per million input tokens and $8.15 per million output tokens.

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