Preference · Meta AI

Llama 3.3 1.5B on Arena Elo: score, rank and what it means

Llama 3.3 1.5B scores 1203.1 on Arena Elo, placing it #549 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
1203.1
0–100 scale
Rank
#549
of 600
Percentile
9th
within the index
Benchmark avg
1349.9
all models
Leader
1501.9
Claude Opus 4.5 Max
Gap to leader
298.8
points

Score distribution

The chart shows the top 10 models on Arena Elo, with Llama 3.3 1.5B 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 3.3 1.5B sits at #549 of 600. The leader, Claude Opus 4.5 Max, scores 1501.9, so the gap to the top is 298.8 points. The median model in this index scores 1373.8, which puts Llama 3.3 1.5B below the midpoint.

Meta AI models average 1342.5 on this benchmark. Llama 3.3 1.5B is 139.4 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 1224.7. Llama 3.3 1.5B is 21.6 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 1203.1 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 $0.61 per million input tokens, Llama 3.3 1.5B is below 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
Llama 3 DeepInfra 1.5B DeepInfra 32768 $0.48 48.8
Magistral 1.5B Mistral AI 4096 $0.67 52.7
Embed 4 Nano Cohere 8192 $1.48 49.7
MiniMax-Text 1.5B MiniMax 32768 $0.58 51.5
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2
Nemotron 4 1.5B NVIDIA 32768 $0.49 50.8
Seed-OSS 1.5B ByteDance 4096 $0.45 49.8

Other benchmarks for Llama 3.3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.0 537 11th
GPQA Diamond 46.1 557 7th
SWE-bench Verified 37.6 539 10th
HumanEval 57.3 529 12th
MATH-500 51.8 543 10th
AIME 2025 40.7 540 10th
LiveCodeBench 40.1 538 10th
IFEval 64.6 535 11th
TruthfulQA 56.7 556 7th
HellaSwag 68.7 550 8th
MMMU 51.4 540 10th

FAQ

What score does Llama 3.3 1.5B get on Arena Elo?

Llama 3.3 1.5B scores 1203.1 on Arena Elo in this index. The benchmark average is 1349.9 and the top score is 1501.9.

How does Llama 3.3 1.5B rank on Arena Elo?

It ranks #549 of 600 models, in the 9th percentile. The leader is Claude Opus 4.5 Max at 1501.9.

Is Llama 3.3 1.5B good at Arena Elo?

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 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 3.3 1.5B cost?

Llama 3.3 1.5B costs $0.61 per million input tokens and $2.59 per million output tokens.

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