NVIDIA
Nemotron Nano 8B
18.1K下载量221点赞Mar 2025发布日期131K tokens上下文NVIDIA Open Model许可证82 优秀质量
Nemotron Nano 8B (8B parameters) requires approximately 8.6 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 10 GB of VRAM.
快速开始
— 复制粘贴即可本地运行Copy-paste commands to run Nemotron Nano 8B on your machine.
Run
lms load Llama-3.1-Nemotron-Nano-8B-v1 && lms server startQuick specs
Parameters8B
Architecturedense
Context131K tokens
Modalitytext
Min RAM3.1 GB
Rec. RAM4.9 GB (Q4_K_M)
LicenseNVIDIA Open Model
FamilyNemotron
✓ Chat✓ Reasoning
About this model
- •Switchable reasoning: toggle detailed thinking on/off via system prompt
- •95.4% on MATH-500 with reasoning on, 36.6% with reasoning off
- •Derived from Llama 3.1 8B with multi-phase post-training
- •Fits on a single RTX GPU for local inference
相关模型
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最佳硬件
Nemotron Nano 8B 的最佳选择
运行此模型
量化选项
各量化级别的 VRAM 估算
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | — |
Q3_K_S | 3 | 3.9 GB | Low | — |
NVFP4 | 4 | 4.5 GB | Medium | — |
Q4_K_M | 4 | 4.9 GB | Medium | — |
Q5_K_M | 5 | 5.8 GB | High | — |
Q6_K | 6 | 6.6 GB | High | — |
Q8_0 | 8 | 8.6 GB | Very High | — |
F16 | 16 | 16.4 GB | Maximum | — |
Quality benchmarks
Nemotron Nano 8B benchmark scores
Reasoning
MMLU-Pro—
GPQA Diamond54.1%
MATH-50095.4%
ARC Challenge—
General
Chatbot Arena—
IFEval74.7%
Source: official · 2025-03-18
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights4.9 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — Nemotron Nano 8B
另请参阅