NVIDIA
Nemotron 3 Super 120B
Open weightopen-weightNVIDIA's flagship 120B/12B-active LatentMoE model with 1M context, trained on 25T tokens. Strong on agentic workflows, reasoning, and long-context tasks. Requires 8x H100-80GB.
Capability profile
Radar view of the model's practical strengths. This chart is backed by textual summaries below for crawlability.
Benchmark summary
Scores 90.21 on AIME25, 60.47 on SWE-Bench, and maintains 91.75 accuracy at 1M context on RULER.
No benchmark series is attached to this model yet. Source links and product metadata are available below.
Strengths
- • 1M token context
- • LatentMoE efficiency
- • Strong agentic capability
- • Multilingual (7 languages)
- • Configurable reasoning mode
Trade-offs
- • Requires 8x H100+
- • Large model size
- • Recent release
Crawlable benchmark analysis
Nemotron 3 Super 120B is positioned as an enterprise llm model with published scores that emphasize its practical fit for buyers evaluating the entry.
Published scores highlight reasoning 88/100, coding 82/100, enterprise readiness 88/100, vision 40/100, speed 72/100, and safety 80/100.
Pricing is not fully published for this entry. With a context window of 1,048,576 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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