Coding · Meta AI

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

Llama 4 Scout scores 70.4 on SWE-bench Verified, placing it #103 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
70.4
0–100 scale
Rank
#103
of 600
Percentile
83th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
11.3
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Llama 4 Scout 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 Scout sits at #103 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 11.3 points. The median model in this index scores 61.0, which puts Llama 4 Scout above the midpoint.

Meta AI models average 56.9 on this benchmark. Llama 4 Scout is 13.5 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 Scout is 4.0 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 70.4 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 $4.90 per million input tokens, Llama 4 Scout 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
Command A Cohere 200000 $13.30 79.6
GLM-4.6 Instruct Zhipu AI 1000000 $5.15 80.4
Claude Haiku 4.5 Pro Anthropic 1000000 $15.07 80.8
Doubao 1.5 Pro ByteDance 200000 $13.65 79.7
Llama 4 Scout Meta AI 200000 $4.90 79.3
Gemini 2.5 Pro Google DeepMind 200000 $15.20 81.6
Kimi K2 Moonshot AI 128000 $5.85 83.0

Other benchmarks for Llama 4 Scout

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.9 123 80th
GPQA Diamond 74.1 165 73th
HumanEval 86.5 96 84th
MATH-500 81.0 192 68th
AIME 2025 74.2 173 71th
LiveCodeBench 72.1 145 76th
IFEval 86.9 136 77th
TruthfulQA 82.1 128 79th
HellaSwag 88.9 114 81th
MMMU 74.1 188 69th
Arena Elo 1431.8 119 80th

FAQ

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

Llama 4 Scout scores 70.4 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Llama 4 Scout rank on SWE-bench Verified?

It ranks #103 of 600 models, in the 83rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is Llama 4 Scout 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 Scout cost?

Llama 4 Scout costs $4.90 per million input tokens and $24.91 per million output tokens.

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