Coding · Hyperbolic

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

Llama 3 Hyperbolic scores 64.0 on LiveCodeBench, placing it #318 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
64.0
0–100 scale
Rank
#318
of 600
Percentile
47th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
21.1
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3 Hyperbolic 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 Hyperbolic sits at #318 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 21.1 points. The median model in this index scores 64.7, which puts Llama 3 Hyperbolic below the midpoint.

Hyperbolic models average 56.5 on this benchmark. Llama 3 Hyperbolic is 7.5 points above that provider line, so it is a stronger result than the average Hyperbolic model.

Among multimodal models, the average is 70.3. Llama 3 Hyperbolic is 6.3 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 64.0 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 $3.86 per million input tokens, Llama 3 Hyperbolic 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
Mixtral Groq Groq 16384 $3.37 73.1
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
DBRX Databricks 65536 $3.29 73.3
Llama 3 Baseten Chat Baseten 200000 $3.55 73.2
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
QwQ Base Alibaba Cloud 65536 $3.68 74.1
Firesearch Pro Fireworks AI 32768 $7.67 70.4

Other benchmarks for Llama 3 Hyperbolic

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.2 238 60th
GPQA Diamond 72.6 206 66th
SWE-bench Verified 64.4 223 63th
HumanEval 79.3 255 58th
MATH-500 76.3 292 51th
AIME 2025 66.8 316 47th
IFEval 83.7 218 64th
TruthfulQA 75.9 309 49th
HellaSwag 85.3 231 62th
MMMU 73.0 219 64th
Arena Elo 1391.3 245 59th

FAQ

What score does Llama 3 Hyperbolic get on LiveCodeBench?

Llama 3 Hyperbolic scores 64.0 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3 Hyperbolic rank on LiveCodeBench?

It ranks #318 of 600 models, in the 47th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3 Hyperbolic 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 Hyperbolic cost?

Llama 3 Hyperbolic costs $3.86 per million input tokens and $19.72 per million output tokens.

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