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NVIDIA · MODEL RELEASE TRACKER
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning is a Mixture-of-Experts (MoE) model with a 30B total-parameter size that activates 3B parameters per token. Reported results include 86% accuracy on PinchBench and completing tasks 30% faster than comparable models. It is available for interactive evaluation on build.nvidia.com, with weights on Hugging Face and API access via OpenRouter. MoE-specific cautions include router-imbalance risks during fine-tuning and different quantization effects on router and recurrent-projection layers.CURRENT SNAPSHOT2/5 DIMENSIONS WITH DATA
The dimensions that change the decision.
Not established from the available sources.
Not established from the available sources.
PinchBench accuracy and task speedReported 86% accuracy on PinchBench while completing tasks 30% faster than comparable models.
Interactive evaluation availabilityAvailable to try interactively on build.nvidia.com.
VERIFIABLE FACTS
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BENCHMARKS · PinchBench accuracy and task speedDEVELOPER CLAIM
Reported 86% accuracy on PinchBench while completing tasks 30% faster than comparable models.
CAPABILITIES · Mixture-of-Experts parameter activationDEVELOPER CLAIM
Uses a Mixture-of-Experts architecture that activates 3B of its 30B total parameters per token.
CAPABILITIES · Throughput relative to dense modelsDEVELOPER CLAIM
At equal total parameter counts, achieves higher token throughput than comparable dense models (e.g., Gemma 4 31B), though latency advantage narrows at high concurrency.
CAPABILITIES · Total parameter countDEVELOPER CLAIM
Total parameter count reported as 30B.
AVAILABILITY · Interactive evaluation availabilityDEVELOPER CLAIM
Available to try interactively on build.nvidia.com.
LIMITATIONS · Fine-tuning and quantization caveatsDEVELOPER CLAIM
Fine-tuning MoE models requires care to avoid router imbalance; quantization affects router and recurrent-projection layers differently than dense-model components.
WHAT CHANGED