Coding · Meta AI

Llama 3.3 8B on LiveCodeBench: score, rank and what it means

Llama 3.3 8B scores 50.5 on LiveCodeBench, placing it #443 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
50.5
0–100 scale
Rank
#443
of 600
Percentile
26th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
34.6
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3.3 8B highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Llama 3.3 8B sits at #443 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 34.6 points. The median model in this index scores 64.7, which puts Llama 3.3 8B below the midpoint.

Meta AI models average 59.3 on this benchmark. Llama 3.3 8B is 8.8 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 41.2. Llama 3.3 8B is 9.3 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 50.5 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 $1.26 per million input tokens, Llama 3.3 8B is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7
Firesearch Mini Fireworks AI 32768 $3.94 61.5
Reka Flash Nano Reka AI 16384 $3.93 61.0
Llama 3.1 Turbo 8B Together AI 32768 $1.16 58.8
Llama 3.3 8B Meta AI 8192 $1.26 60.1
Kimi K2 7B Moonshot AI 16384 $1.72 62.7
Qwen3 7B Alibaba Cloud 32768 $1.37 59.8

Other benchmarks for Llama 3.3 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 62.5 496 17th
GPQA Diamond 54.2 477 21th
SWE-bench Verified 45.5 459 24th
HumanEval 64.2 450 25th
MATH-500 59.0 477 21th
AIME 2025 53.5 428 29th
IFEval 70.2 457 24th
TruthfulQA 65.9 445 26th
HellaSwag 75.8 430 28th
MMMU 60.1 427 29th
Arena Elo 1272.0 455 24th

FAQ

What score does Llama 3.3 8B get on LiveCodeBench?

Llama 3.3 8B scores 50.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3.3 8B rank on LiveCodeBench?

It ranks #443 of 600 models, in the 26th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3.3 8B good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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 3.3 8B cost?

Llama 3.3 8B costs $1.26 per million input tokens and $5.56 per million output tokens.

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