Coding · Cerebras

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

Llama 3.1 Cerebras Chat scores 68.3 on LiveCodeBench, placing it #221 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
68.3
0–100 scale
Rank
#221
of 600
Percentile
63th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
16.8
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3.1 Cerebras Chat 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 Chat sits at #221 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 16.8 points. The median model in this index scores 64.7, which puts Llama 3.1 Cerebras Chat above the midpoint.

Cerebras models average 57.6 on this benchmark. Llama 3.1 Cerebras Chat is 10.7 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 Chat is 2.0 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 68.3 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 $4.07 per million input tokens, Llama 3.1 Cerebras Chat 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
Sonar Perplexity 200000 $10.57 76.0
Llama 3.3 Meta AI 128000 $4.56 78.2
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2
Llama 3 Novita Instruct Novita AI 32768 $3.94 75.6
Llama 3.1 Cerebras Chat Cerebras 32768 $4.07 76.0
Llama 4 Scout Chat Meta AI 32768 $4.66 78.0
DeepSeek-Coder DeepSeek 32768 $4.55 78.1

Other benchmarks for Llama 3.1 Cerebras Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.6 191 68th
GPQA Diamond 69.7 275 54th
SWE-bench Verified 64.6 219 64th
HumanEval 82.5 175 71th
MATH-500 77.4 270 55th
AIME 2025 74.1 177 71th
IFEval 83.5 229 62th
TruthfulQA 78.4 241 60th
HellaSwag 84.7 260 57th
MMMU 73.1 218 64th
Arena Elo 1391.6 243 60th

FAQ

What score does Llama 3.1 Cerebras Chat get on LiveCodeBench?

Llama 3.1 Cerebras Chat scores 68.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3.1 Cerebras Chat rank on LiveCodeBench?

It ranks #221 of 600 models, in the 63rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3.1 Cerebras Chat 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 Chat cost?

Llama 3.1 Cerebras Chat costs $4.07 per million input tokens and $16.82 per million output tokens.

Related