nvidia · nemotron_h
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 by nvidia: a 31.6B-parameter mixture-of-experts open-weight model under the other license with tool calling.
897,899 downloads · 824 likes · Model card · synced 2026-10-05
Specifications
- Parameters
- 31.6B (1.5B active)
- Architecture
- moe · nemotron_h
- Layers
- 52
- Hidden size
- 2,688
- KV heads · head dim
- 2 · 128
- Vocabulary
- 131,072
- Native dtype
- bfloat16
- Context window
- 262,144 tokens
- Released
- 2025-12-04
- Last modified on Hub
- 2026-08-24
Features & licensing
- License
- other
- Commercial use
- No
- Modalities
- text
- Tool / function calling
- Yes
- Reasoning mode
- Yes
- Languages
- EN, ES, FR, DE, JA, IT
- Quantised variants on Hub
- —
- Pipeline
- text-generation
Task fit
Editorial scores (0–100) used by the recommendation engine.
- Chat70
- RAG / Q&A70
- Code70
- Summarisation70
- Extraction70
- Agents70
Hardware to run NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
Weights need about 70 GB at FP16, 36 GB at INT8 and 21 GB at INT4. The KV cache adds roughly 53 MB per 1,000 tokens per request. For a reference workload of 5 requests per second with 1,500 input and 300 output tokens, total GPU memory is around 26.9 GB, which fits on 1 × NVIDIA A100 (80 GB).
| Configuration | VRAM | Utilisation | Est. first token | Cloud / month |
|---|---|---|---|---|
| 2 × NVIDIA L4 (24 GB) | 48 GB | 56 % | ~0.5 s | $1,168 |
| 1 × NVIDIA L40S (48 GB) | 48 GB | 56 % | ~0.2 s | $1,387 |
| 1 × NVIDIA A100 (80 GB)recommended | 80 GB | 34 % | ~0.1 s | $2,336 |
| 1 × NVIDIA H100 (80 GB) | 80 GB | 34 % | ~0.0 s | $3,285 |
Estimates only. Run an assessment for your own traffic.
Auto-imported from Hugging Face. Architecture, license and feature data are synced from the model repository; the task-fit scores below are provisional defaults until a curator reviews them.