Coding · Novita AI

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

Llama 3 Novita Chat scores 66.5 on LiveCodeBench, placing it #263 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
66.5
0–100 scale
Rank
#263
of 600
Percentile
56th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
18.6
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Llama 3 Novita 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 Novita Chat sits at #263 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 18.6 points. The median model in this index scores 64.7, which puts Llama 3 Novita Chat above the midpoint.

Novita AI models average 55.6 on this benchmark. Llama 3 Novita Chat is 10.9 points above that provider line, so it is a stronger result than the average Novita AI model.

Among multimodal models, the average is 70.3. Llama 3 Novita Chat is 3.8 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 66.5 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 $3.50 per million input tokens, Llama 3 Novita Chat 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
Fusion Reasoning OpenRouter 65536 $8.59 72.2
Gemini 3 Pro Nano Google DeepMind 8192 $9.11 73.2
Reka Flash Max Reka AI 32768 $11.17 75.9
Grok 4 Nano xAI 16384 $8.97 72.7
Llama 3 Novita Chat Novita AI 65536 $3.50 74.2
Llama 3.1 Turbo Base Together AI 16384 $3.30 73.0
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7

Other benchmarks for Llama 3 Novita Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.5 291 52th
GPQA Diamond 69.8 271 55th
SWE-bench Verified 61.6 290 52th
HumanEval 77.8 291 52th
MATH-500 76.1 296 51th
AIME 2025 72.0 219 64th
IFEval 82.1 274 54th
TruthfulQA 78.9 223 63th
HellaSwag 83.5 306 49th
MMMU 71.5 256 57th
Arena Elo 1368.4 324 46th

FAQ

What score does Llama 3 Novita Chat get on LiveCodeBench?

Llama 3 Novita Chat scores 66.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Llama 3 Novita Chat rank on LiveCodeBench?

It ranks #263 of 600 models, in the 56th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Llama 3 Novita 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 Novita Chat cost?

Llama 3 Novita Chat costs $3.50 per million input tokens and $17.98 per million output tokens.

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