Model reference · open weights
NVIDIA-Nemotron-3.5-Lightning-DSpark is an open-weight language model from nvidia, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Model Overview Description: The NVIDIA Nemotron-3.5-Lightning-30B-A3B-NVFP4-DSpark model is the DSpark speculative decoding checkpoint for NVIDIA's Nemotron-3.5-Lightning-30B-A3B model family, which is a hybrid LatentMoE language model designed for reasoning, chat, and agentic workflows. For more information, please check BF16, NVFP4. The NVIDIA Nemotron-3.5-Lightning-30B-A3B-DSpark-NVFP4 model is intended for DSpark speculative decoding deployments tuned for DGX Spark and low-concurrency data centre workflows. This model is ready for commercial or non-commercial use. License/Terms of Use: GOVERNING DOWNLOAD TERMS: Use of this model is governed by the OpenMDW-1.1 model license. Deployment Geography: Global Use Case: Developers deploying Nemotron-3.5-Lightning-30B-A3B for reasoning, chat, RAG, and agentic workflows that benefit from lower-latency speculative decoding on DGX Spark and data centre GPUs. This release is intended for DSpark-assisted serving of Nemotron-3.5-Lightning-30B-A3B rather than as a standalone target model checkpoint. Release Date: Hugging Face 08/11/2026 via https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4-DSpark References - NVIDIA Model Optimizer: https://github.com/NVIDIA/Model-Optimizer - NVIDIA Nemotron-3.5-Lightning-30B-A3B-BF16 reasoning model card - NVIDIA Nemotron-3.5-Lightning-30B-A3B-NVFP4 reasoning model card - OpenMDW License Agreement, version 1.1 - DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation Model Architecture: The DSpark model architecture is as follows: Architecture Type: Dense GQA (Dense MLP + GQA Attention) Network Architecture: Dense FFN MLP, and GQA Attention layers; DSpark speculative decoding attention uses causal grouped-query attention (GQA) with a sliding window of size 1024 on all layers, and per-head attention sink bias. Number of Model Parameters: 967M total parameters, of which 615M are non-embedding parameters. For more information about the underlying model's architecture, please see this Nemotron-3.5-Lightning-30B-A3B-BF16, Nemotron-3.5-Lightning-30B-A3B-NVFP4. Input: Input Type(s): Text Input Format(s): String Input Parameters: One-Dimensiona
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | nvidia |
|---|---|
| Type | Language models |
| Parameters (lead) | 764M |
| Variants | 1 |
| Runs with | Model Optimizer |
| Based on | nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16, nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4 |
| Released | 2026-08-05 |
| Popularity | 191k downloads / month |
| Likes | 22 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4-DSpark | 764M | NVFP4 | — | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys nvidia-nemotron-3-5-lightning-dspark for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (nvidia-nemotron-3-5-lightning-dspark below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"nvidia-nemotron-3-5-lightning-dspark","messages":[{"role":"user","content":"Hello"}]}'
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗
Sources