SAVRN Model Hub · Comparisons
NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 vs Qwen3.6-35B-A3B-NVFP4
NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 has 18.2B parameters and Qwen3.6-35B-A3B-NVFP4 has 18.7B parameters; NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 is released under other and Qwen3.6-35B-A3B-NVFP4 under Apache License 2.0; at 16-bit, NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 needs about 43.8 GB (1x MI300X from $1.85 an hour) and Qwen3.6-35B-A3B-NVFP4 about 44.8 GB (1x MI300X from $1.85 an hour).
| Field | NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 | Qwen3.6-35B-A3B-NVFP4 nvidia/Qwen3.6-35B-A3B-NVFP4 |
|---|---|---|
| Publisher | NVIDIA | NVIDIA |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 18.2B parameters | 18.7B parameters |
| Architecture | NemotronHForCausalLM | Qwen3_5MoeForConditionalGeneration |
| Library | transformers | Model Optimizer |
| Context length | 262,144 tokens | 262,144 tokens |
| Repository size | 19.4 GB | 23.5 GB |
| Artifact formats | safetensors, pytorch | safetensors |
| License | other | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 43.8 GB | 44.8 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 10.9 GB | 11.2 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 6efb4a2a1c1f | 1355db6a0524 |
| Downloads reported by the hub | 730.6k | 8.4M |
| Last observed | 2026-09-18 | 2026-09-18 |
An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.
SAVRN's Notes on NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4
Start with the context: 262,144 tokens. NVIDIA built Nemotron 3 Nano as a single model for both reasoning and non-reasoning work: it writes a reasoning trace first, then the answer, and a flag in the chat template turns the reasoning on or off. This NVFP4 build is the quantized version of the BF16 release, with 128 routed experts. At 4-bit the weights are 9.1 GB and the run needs 10.9 GB, so the cheapest listed setup, one MI300X with 192 GB at $1.85 an hour, leaves most of the card for context.
The license is listed as other with no summary on the page, so read NVIDIA's terms yourself before this goes near a product. Check the dates too: pre-training cutoff June 25, 2025, post-training November 28, 2025. The seven Nemotron training sets are named on the page, so you can see what went in.
SAVRN's Notes on Qwen3.6-35B-A3B-NVFP4
NVIDIA's part in this one is the quantization, not the model. It ran Alibaba's Qwen3.6-35B-A3B through Model Optimizer, and its own card says NVIDIA neither owns nor developed the result: 18.7B parameters as a mixture of 256 experts, 8 active per token. Our sizing wants 44.8 GB of memory at 16-bit and 11.2 GB at 4-bit; the cheapest setup we list is one 192 GB MI300X at $1.85 per hour on-demand, and the 262,144 token context is where the rest of that card goes on real jobs.
Before committing, read Alibaba's card for the parent Qwen3.6-35B-A3B, since that is what you are deploying. Apache 2.0 covers commercial use, modification and redistribution, provided the license and NOTICE file stay attached and significant changes are stated. Files were last updated August 29, 2026, three months after the May 27 release, so confirm which revision you pulled.
Questions
Which is larger, NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 or Qwen3.6-35B-A3B-NVFP4?
Qwen3.6-35B-A3B-NVFP4 (18.7B parameters) is larger than NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 (18.2B parameters), by the parameter counts their publishers report.
Which is cheaper to run, NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 or Qwen3.6-35B-A3B-NVFP4?
At 4-bit, NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 fits on 1x MI300X from $1.85 an hour and Qwen3.6-35B-A3B-NVFP4 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Qwen3.6-35B-A3B-NVFP4 commercially?
Yes. Qwen3.6-35B-A3B-NVFP4 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.