Nvidia Nemotron 3.5 Lightning
Nvidia Nemotron 3.5 Lightning is an open-weight 30B-A3B hybrid Mamba-Transformer mixture-of-experts model for high-throughput agentic, coding, tool-use, instruction-following, and long-context workloads. Thinking is disabled on this variant.
- Reasoning
- Tool Calling
- Parallel Tool Calls
Added Aug 12, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.05
- Output
- $0.20
- Cache read
- $0.01
Specifications
- Context window
- 1M
- Max output
- 65.5K
- Parameters
- 30B / 3B
- Total / active
- Avg output (7d)
- 140 tokens
- Longer than 15% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
5.5
Coding Index
26.8
Agentic Index
3.5
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
0.8%
Better than 11% of models compared
AutomationBench-AA Tasks Completed
Fully completed workflows without guardrail violations
0.0%
Better than 7% of models compared
AA-Briefcase v1.1
Agentic knowledge work (Elo)
507 Elo
Better than 21% of models compared
GDPval-AA v2.1
Economically valuable tasks (Elo)
646 Elo
Better than 29% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
3.0%
Better than 18% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
60.3%
Better than 49% of models compared
MLCR-AA
Medical long-context reasoning
2.2%
Better than 5% of models compared
Reasoning
HLE
Humanity's Last Exam
10.6%
Better than 50% of models compared
CritPt
Research-level physics reasoning
0.0%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
0.5%
Better than 33% of models compared
SciCode
Python programming for scientific computing
32.1%
Better than 10% of models compared
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
74.3%
Better than 55% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
60.3%
Better than 49% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
7.3%
Last updated Nov 1, 2026
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