NVIDIA
Nemotron-Cascade 2
Open weightopen-weightNVIDIA's 32B (30B-A3B MoE) Nemotron-Cascade 2 trained with cascade RL and multi-domain on-policy distillation. 74.8K downloads on HuggingFace.
Capability profile
Radar view of the model's practical strengths. This chart is backed by textual summaries below for crawlability.
Benchmark summary
Trained with novel cascade RL approach achieving strong reasoning with efficient MoE architecture.
No benchmark series is attached to this model yet. Source links and product metadata are available below.
Strengths
- • Cascade RL training
- • MoE efficiency
- • Strong reasoning
- • Published research paper
Trade-offs
- • Smaller than Super 120B
- • Less community adoption
Crawlable benchmark analysis
Nemotron-Cascade 2 is positioned as an enterprise llm model with published scores that emphasize its practical fit for buyers evaluating the entry.
Published scores highlight reasoning 82/100, coding 78/100, enterprise readiness 85/100, vision 35/100, speed 80/100, and safety 78/100.
Pricing is not fully published for this entry. With a context window of 131,072 tokens, it supports large-document analysis and retrieval workflows.
Benchmark coverage is still limited for this entry, so this section focuses on published metadata and deployment fit.
Sources
Provider and distribution links used to verify this model record.
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