Coding · NVIDIA

Nemotron Nano Instruct on LiveCodeBench: score, rank and what it means

Nemotron Nano Instruct scores 57.1 on LiveCodeBench, placing it #395 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
57.1
0–100 scale
Rank
#395
of 600
Percentile
34th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
28.0
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Nemotron Nano Instruct 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, Nemotron Nano Instruct sits at #395 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 28.0 points. The median model in this index scores 64.7, which puts Nemotron Nano Instruct below the midpoint.

NVIDIA models average 51.3 on this benchmark. Nemotron Nano Instruct is 5.8 points above that provider line, so it is a stronger result than the average NVIDIA model.

Among open-weight models, the average is 59.1. Nemotron Nano Instruct 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 57.1 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 $2.33 per million input tokens, Nemotron Nano Instruct 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
Molmo Instruct Allen Institute for AI 32768 $2.53 68.3
Grok 3 Nano xAI 8192 $7.12 67.8
Firesearch Fireworks AI 32768 $7.03 68.5
Molmo Allen Institute for AI 32768 $2.49 68.5
Nemotron Nano Instruct NVIDIA 32768 $2.33 67.4
Embed 4 Reasoning Cohere 4096 $5.50 65.3
SmolLM3 Instruct Hugging Face 8192 $1.69 63.6

Other benchmarks for Nemotron Nano Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.6 371 38th
GPQA Diamond 64.7 366 39th
SWE-bench Verified 54.5 388 35th
HumanEval 72.9 375 38th
MATH-500 67.4 404 33th
AIME 2025 58.6 396 34th
IFEval 75.2 396 34th
TruthfulQA 73.0 369 39th
HellaSwag 79.7 384 36th
MMMU 66.2 368 39th
Arena Elo 1331.2 387 36th

FAQ

What score does Nemotron Nano Instruct get on LiveCodeBench?

Nemotron Nano Instruct scores 57.1 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Nemotron Nano Instruct rank on LiveCodeBench?

It ranks #395 of 600 models, in the 34th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Nemotron Nano Instruct 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 Nemotron Nano Instruct cost?

Nemotron Nano Instruct costs $2.33 per million input tokens and $11.92 per million output tokens.

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