Coding · Hyperbolic

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

Llama 3 Hyperbolic Base scores 62.5 on LiveCodeBench, placing it #341 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
62.5
0–100 scale
Rank
#341
of 600
Percentile
43th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
22.6
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3 Hyperbolic Base 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 Base sits at #341 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 22.6 points. The median model in this index scores 64.7, which puts Llama 3 Hyperbolic Base below the midpoint.

Hyperbolic models average 56.5 on this benchmark. Llama 3 Hyperbolic Base is 6.0 points above that provider line, so it is a stronger result than the average Hyperbolic model.

Among open-weight models, the average is 59.1. Llama 3 Hyperbolic Base is 3.4 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 62.5 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 $3.02 per million input tokens, Llama 3 Hyperbolic Base 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
Auto Pro OpenRouter 8192 $8.41 71.2
Yi-Large 01.AI 32768 $3.40 73.5
Yi-Large Chat 01.AI 65536 $3.49 73.5
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Mixtral Mistral AI 65536 $3.48 73.7
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7

Other benchmarks for Llama 3 Hyperbolic Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 73.3 366 39th
GPQA Diamond 64.3 375 38th
SWE-bench Verified 58.2 353 41th
HumanEval 74.3 354 41th
MATH-500 77.1 275 54th
AIME 2025 69.3 272 55th
IFEval 79.0 355 41th
TruthfulQA 72.5 375 38th
HellaSwag 83.3 313 48th
MMMU 68.6 332 45th
Arena Elo 1369.8 317 47th

FAQ

What score does Llama 3 Hyperbolic Base get on LiveCodeBench?

Llama 3 Hyperbolic Base scores 62.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3 Hyperbolic Base rank on LiveCodeBench?

It ranks #341 of 600 models, in the 43rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3 Hyperbolic Base 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 Base cost?

Llama 3 Hyperbolic Base costs $3.02 per million input tokens and $10.87 per million output tokens.

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