Coding · Baseten

Llama 3 Baseten 8B on LiveCodeBench: score, rank and what it means

Llama 3 Baseten 8B scores 44.3 on LiveCodeBench, placing it #504 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
44.3
0–100 scale
Rank
#504
of 600
Percentile
16th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
40.8
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3 Baseten 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 Baseten 8B sits at #504 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 40.8 points. The median model in this index scores 64.7, which puts Llama 3 Baseten 8B below the midpoint.

Baseten models average 54.7 on this benchmark. Llama 3 Baseten 8B is 10.4 points below that provider line, so it is a weaker result than the average Baseten model.

Among small open-weight models, the average is 41.2. Llama 3 Baseten 8B is 3.1 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 44.3 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 $1.02 per million input tokens, Llama 3 Baseten 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
Command R+ 7B Cohere 8192 $0.95 56.2
Seed-OSS 7B ByteDance 8192 $0.85 55.5
Llama 3.3 Groq 7B Groq 16384 $1.01 56.7
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Llama 3 Baseten 8B Baseten 4096 $1.02 57.0
QwQ 7B Alibaba Cloud 8192 $1.11 58.1
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4

Other benchmarks for Llama 3 Baseten 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 63.6 481 20th
GPQA Diamond 54.9 465 23th
SWE-bench Verified 44.9 466 22th
HumanEval 61.5 474 21th
MATH-500 58.2 487 19th
AIME 2025 44.7 499 17th
IFEval 67.1 501 17th
TruthfulQA 63.1 488 19th
HellaSwag 71.4 512 15th
MMMU 53.8 508 15th
Arena Elo 1269.0 463 23th

FAQ

What score does Llama 3 Baseten 8B get on LiveCodeBench?

Llama 3 Baseten 8B scores 44.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3 Baseten 8B rank on LiveCodeBench?

It ranks #504 of 600 models, in the 16th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3 Baseten 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 Baseten 8B cost?

Llama 3 Baseten 8B costs $1.02 per million input tokens and $5.38 per million output tokens.

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