Nemotron (Nvidia) vs Qwen (Alibaba)

Which one should you pick? Here's the full breakdown.

Nemotron (Nvidia)

B
7.8/10

Nvidia's open-weights family -- hybrid Mamba-Transformer MoE architecture, optimized for efficient reasoning on Nvidia hardware

Our Pick

Qwen (Alibaba)

A
8.8/10

Alibaba's open-weights family -- Qwen3.5, Qwen3-Coder-Next, Qwen3-VL, Qwen3-Max. Apache 2.0 flagship sizes.

CategoryNemotron (Nvidia)Qwen (Alibaba)
Ease of Use6.57.0
Output Quality8.09.0
Value8.010.0
Features8.59.0
Overall7.88.8

Pricing Comparison

FeatureNemotron (Nvidia)Qwen (Alibaba)
Free TierYesYes
Starting Price$0$0

Benchmark Head-to-Head

Nemotron 3 Ultra (253B) vs Qwen3.5-397B MoE

BenchmarkNemotron (Nvidia)Qwen (Alibaba)
MMLU-Pro79.8%83.5%
GPQA Diamond70.5%78.2%
AIME 202584.5%87%
HumanEval89.6%92.5%

Which Should You Pick?

Pick Nemotron (Nvidia) if...

Teams running on Nvidia hardware (TensorRT-LLM, NIM) who need efficient long-context reasoning. Nemotron 3 Super is a standout for its 8 GB VRAM footprint with strong reasoning.

Visit Nemotron (Nvidia)

Pick Qwen (Alibaba) if...

  • Higher output quality (9 vs 8)
  • Better value for money (10/10)
  • Stronger on graduate-level science questions (+7.7% on GPQA Diamond)

Developers who want frontier-tier open weights with Apache 2.0 licensing. Qwen3-Coder-Next is arguably the best local coding model; Qwen3.5-397B is a top-3 open generalist.

Visit Qwen (Alibaba)

Our Verdict

Qwen (Alibaba) is the clear winner here with 8.8/10 vs 7.8/10. Nemotron (Nvidia) isn't bad, but Qwen (Alibaba) outperforms it across the board. Pick Nemotron (Nvidia) only if teams running on nvidia hardware (tensorrt-llm, nim) who need efficient long-context reasoning.