Coding · Cerebras

Llama 3.1 Cerebras on LiveCodeBench: score, rank and what it means

Llama 3.1 Cerebras scores 66.1 on LiveCodeBench, placing it #273 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
66.1
0–100 scale
Rank
#273
of 600
Percentile
55th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
19.0
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3.1 Cerebras 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 3.1 Cerebras sits at #273 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 19.0 points. The median model in this index scores 64.7, which puts Llama 3.1 Cerebras above the midpoint.

Cerebras models average 57.6 on this benchmark. Llama 3.1 Cerebras is 8.5 points above that provider line, so it is a stronger result than the average Cerebras model.

Among multimodal models, the average is 70.3. Llama 3.1 Cerebras is 4.2 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 66.1 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 $4.01 per million input tokens, Llama 3.1 Cerebras is above 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
MiniMax-M2 Base MiniMax 65536 $4.20 76.4
Mixtral Groq Instruct Groq 16384 $3.25 72.5
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Codestral Instruct Mistral AI 65536 $4.01 75.1
Llama 3.1 Cerebras Cerebras 128000 $4.01 76.0
Firefunction Pro Fireworks AI 16384 $9.05 72.9
Llama 3 Replicate Instruct Replicate 128000 $3.71 75.1

Other benchmarks for Llama 3.1 Cerebras

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.4 295 51th
GPQA Diamond 74.4 156 74th
SWE-bench Verified 64.9 214 64th
HumanEval 81.3 204 66th
MATH-500 82.4 155 74th
AIME 2025 69.8 260 57th
IFEval 84.6 199 67th
TruthfulQA 80.6 166 72th
HellaSwag 85.1 239 60th
MMMU 70.1 298 50th
Arena Elo 1411.3 179 70th

FAQ

What score does Llama 3.1 Cerebras get on LiveCodeBench?

Llama 3.1 Cerebras scores 66.1 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3.1 Cerebras rank on LiveCodeBench?

It ranks #273 of 600 models, in the 55th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3.1 Cerebras 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 3.1 Cerebras cost?

Llama 3.1 Cerebras costs $4.01 per million input tokens and $15.13 per million output tokens.

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