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Llama 3.1 Nemotron Nano 4B V1.1 (Reasoning)
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Llama 3.1 Nemotron Nano 4B V1.1 (Reasoning)

NVIDIA 與 Meta 合作開發的緊湊推理增強模型，僅 4B 參數但具備強大的推理能力。經過 NVIDIA 優化，在效率和性能之間達到良好平衡。專門針對推理任務進行增強，能夠在資源受限的環境中提供可靠的邏輯分析和問題解決能力，適合邊緣計算和行動裝置上的推理應用。
Intelligence(Medium)
Speed(Slow)
Input Supported Modalities
No
Is Reasoning Model
128,000
Context Window
131,072
Maximum Output Tokens
2023-12-31
Knowledge Cutoff
Go Compare

Pricing

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Input
- /M tokens
Output
- /M tokens
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Input

Output

Llama 3.3 Nemotron Super 49B v1
Llama 3.1 Nemotron Instruct 70B
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)

Basic Parameters

Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)Technical Parameters
Parameter Count
8,000.0M
Context Length
128.00k tokens
Training Data Cutoff
2023-12-31
Open Source Category
Open Weights (Permissive License)
Multimodal Support
Text Only
Throughput
Release Date
2025-05-20
Response Speed
0 tokens/s

Benchmark Scores

Below is the performance of Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
45.01
Large Language Model Intelligence Level
Coding Index
29.69
Indicator of AI model performance on coding tasks
Math Index
82.67
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
55.6
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
40.8
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
5.1
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
49.3
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
10.1
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
-
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
94.7
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
70.7
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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