Coding · Replicate

Llama 3 Replicate on LiveCodeBench: score, rank and what it means

Llama 3 Replicate scores 69.2 on LiveCodeBench, placing it #205 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
69.2
0–100 scale
Rank
#205
of 600
Percentile
66th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
15.9
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3 Replicate 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 Replicate sits at #205 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 15.9 points. The median model in this index scores 64.7, which puts Llama 3 Replicate above the midpoint.

Replicate models average 57.5 on this benchmark. Llama 3 Replicate is 11.7 points above that provider line, so it is a stronger result than the average Replicate model.

Among multimodal models, the average is 70.3. Llama 3 Replicate is 1.1 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 69.2 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 $3.75 per million input tokens, Llama 3 Replicate 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
Reka Flash Pro Reka AI 200000 $10.82 75.2
Reka Core Reka AI 32768 $12.17 77.4
Llama 4 Maverick Base Meta AI 128000 $4.68 79.1
Llama 3 DeepInfra Instruct DeepInfra 65536 $3.84 75.5
Llama 3 Replicate Replicate 200000 $3.75 75.7
Gemini 3 Flash Mini Google DeepMind 200000 $10.71 76.0
Llama 3 Hyperbolic Chat Hyperbolic 200000 $3.64 75.1

Other benchmarks for Llama 3 Replicate

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.8 219 64th
GPQA Diamond 67.7 318 47th
SWE-bench Verified 65.4 207 66th
HumanEval 81.0 214 64th
MATH-500 80.0 206 66th
AIME 2025 72.6 208 65th
IFEval 83.6 224 63th
TruthfulQA 75.5 320 47th
HellaSwag 86.5 192 68th
MMMU 72.5 231 62th
Arena Elo 1373.6 303 50th

FAQ

What score does Llama 3 Replicate get on LiveCodeBench?

Llama 3 Replicate scores 69.2 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3 Replicate rank on LiveCodeBench?

It ranks #205 of 600 models, in the 66th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3 Replicate good at LiveCodeBench?

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 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 Replicate cost?

Llama 3 Replicate costs $3.75 per million input tokens and $13.86 per million output tokens.

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