SAVRN Model Hub · Comparisons
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 vs Qwen3-32B
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 has 31.6B parameters and Qwen3-32B has 32.8B parameters; NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 is released under other and Qwen3-32B under Apache License 2.0; at 16-bit, NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 needs about 75.8 GB (1x MI300X from $1.85 an hour) and Qwen3-32B about 78.6 GB (1x MI300X from $1.85 an hour).
| Field | NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 | Qwen3-32B Qwen/Qwen3-32B |
|---|---|---|
| Publisher | NVIDIA | Qwen |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 31.6B parameters | 32.8B parameters |
| Architecture | NemotronHForCausalLM | Qwen3ForCausalLM |
| Library | transformers | transformers |
| Context length | 262,144 tokens | 40,960 tokens |
| Repository size | 63.2 GB | 65.5 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) | 75.8 GB | 78.6 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 18.9 GB | 19.7 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | bf77c3174f68 | 9216db5781bf |
| Downloads reported by the hub | 704.5k | 5M |
| 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.
Other Reported Results
These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.
NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 86.8 | Liquid AI — IFStruct v1.0 blog (Nemotron-3-Nano-30B-A3B) Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
Qwen3-32B
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| LEXam-Benchmark/LEXam | Task mcq_4_choicesMetric mcq_4_choicesComparison conditions not established | 45.3 | LEXam Leaderboard Reported by a third party |
Evaluated revision not stated | 2026-06-02 |
| LEXam-Benchmark/LEXam | Task open_questionMetric open_questionComparison conditions not established | 40 | LEXam Leaderboard Reported by a third party |
Evaluated revision not stated | 2026-06-02 |
SAVRN's Notes on NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
Seventy-six gigabytes is the number that decides the hardware here. At 16-bit the 31.6B parameters need 75.8 GB, which fits on a single MI300X with 192 GB at $1.85 per hour, the cheapest setup the Index prices, with room left for the 262,144-token context. At 8-bit the need drops to 37.9 GB and at 4-bit to 18.9 GB, and all 128 routed experts are in that bill. NVIDIA trained it for reasoning and non-reasoning work: it writes a reasoning trace before its answer, and a chat template flag turns the trace off.
The license field says other and we have no summary of its terms on file, so read NVIDIA's license in full before any commercial deployment. Two more checks: the one reported score, 86.8 on Liquid AI's IFStruct v1.0, is third-party reported, and pre-training data stops at June 25, 2025. No Index host serves it by the token yet.
Questions
Which is larger, NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 or Qwen3-32B?
Qwen3-32B (32.8B parameters) is larger than NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 (31.6B parameters), by the parameter counts their publishers report.
Which is cheaper to run, NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 or Qwen3-32B?
At 4-bit, NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 fits on 1x MI300X from $1.85 an hour and Qwen3-32B on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Qwen3-32B commercially?
Yes. Qwen3-32B 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.