NVIDIA-Nemotron-3-Nano-4B-BF16 vs Qwen3-4B-Thinking-2507
Specs, VRAM requirements and download trends — updated 21 September 2026.
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | NVIDIA-Nemotron-3-Nano-4B-BF16 | Qwen3-4B-Thinking-2507 |
|---|---|---|
| Parameters | 4.0 B | 4.0 B |
| Architecture | NemotronHForCausalLM | Qwen3ForCausalLM |
| Context length | 262,144 | 262,144 |
| Licence | other | apache-2.0 |
| Commercial use | Unknown | Allowed |
| Languages | 1 | — |
| Downloads 30d | 3,492,652 | 419,975 |
| Downloads all time | 6.9 M | 7.4 M |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2026-03-07 | 2025-08-05 |
Download trend
Daily snapshots, last 56 days (28 Jul – 21 Sep)
3.5 M307 K
NVIDIA-Nemotron-3-Nano-4B-BF16
Qwen3-4B-Thinking-2507
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
NVIDIA-Nemotron-3-Nano-4B-BF16 · fp16 @ 256K ctx
28.3 GB / 24 GB
Qwen3-4B-Thinking-2507 · fp16 @ 256K ctx
28.6 GB / 24 GB
Adjacent comparisons
Qwen3-4B vs NVIDIA-Nemotron-3-Nano-4B-BF16
Qwen3-8B vs NVIDIA-Nemotron-3-Nano-4B-BF16
Qwen2.5-7B-Instruct vs NVIDIA-Nemotron-3-Nano-4B-BF16
Qwen3-4B-Instruct-2507 vs NVIDIA-Nemotron-3-Nano-4B-BF16
Qwen2.5-3B-Instruct vs NVIDIA-Nemotron-3-Nano-4B-BF16
Llama-3.1-8B-Instruct vs NVIDIA-Nemotron-3-Nano-4B-BF16