nvidia · Open weights
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
- Tools
- Parallel tools
- Input
- Text
- Output
- Text
- Reasoning effort
- none · high
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.05
- Output
- $0.20
- Cache read
- $0.01
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 65.5K
- Average output (7 days)
- 228 tokens
- Longer than 24% of 468 models
Side by side
Nvidia Nemotron 3.5 Lightning compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Nvidia Nemotron 3.5 LightningnvidiaThis model | Nvidia Nemotron 3.5 Super VLnvidiaRemove | |
|---|---|---|
| Provider | nvidia | nvidia |
| Discovery tier | Open weights | Open weights |
| Added | Aug 12, 2026 | Oct 15, 2026 |
| Limits | ||
| Context window | 1MBest | 262.14K |
| Max output | 65.54KBest | 16.38K |
| Average output | 228 tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.05Best | $0.15 |
| Output | $0.20Best | $0.50 |
| Cache read | $0.01Best | $0.02 |
| Performance | ||
| Throughput | 536.8 tok/s | 654.7 tok/sBest |
| Time to first token | 0.9 sBest | 1.8 s |
| Request success (24h) | 100.0%Best | 98.0% |
| Benchmark indexes | ||
| Intelligence Index | 12.9 | 26.5Best |
| Coding Index | 26.8 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| Video input | No | Yes |
| Parallel tools | Yes | No |
| Reasoning effort | none, high | none, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Nvidia Nemotron 3.5 Lightning
- Nvidia Nemotron 3.5 Super VL
Intelligence Index
- Nvidia Nemotron 3.5 Lightning12.9
- Nvidia Nemotron 3.5 Super VL26.5
Nvidia Nemotron 3.5 Lightning: Better than 30% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Nvidia Nemotron 3.5 Lightning: 26.8
- Nvidia Nemotron 3.5 Super VL: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Nvidia Nemotron 3.5 Lightning: 0.8%
- Nvidia Nemotron 3.5 Super VL: 14.8%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Nvidia Nemotron 3.5 Lightning: 0.0%
- Nvidia Nemotron 3.5 Super VL: 2.0%Top
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Nvidia Nemotron 3.5 Lightning: 506 Elo
- Nvidia Nemotron 3.5 Super VL: 999 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Nvidia Nemotron 3.5 Lightning: 638 Elo
- Nvidia Nemotron 3.5 Super VL: 1,162 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Nvidia Nemotron 3.5 Lightning: 3.0%
- Nvidia Nemotron 3.5 Super VL: 8.0%Top
AA-LCRv1.1
Reasoning across long documents
- Nvidia Nemotron 3.5 Lightning: 60.3%
- Nvidia Nemotron 3.5 Super VL: 69.0%Top
MLCR-AA
Long-context reasoning over medical records
- Nvidia Nemotron 3.5 Lightning: 2.2%
- Nvidia Nemotron 3.5 Super VL: 13.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Nvidia Nemotron 3.5 Lightning: 10.6%
- Nvidia Nemotron 3.5 Super VL: 30.7%Top
GPQA Diamond
Graduate-level science questions
- Nvidia Nemotron 3.5 Lightning: 74.3%
- Nvidia Nemotron 3.5 Super VL: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Nvidia Nemotron 3.5 Lightning: 0.5%Top
- Nvidia Nemotron 3.5 Super VL: 0.0%
SciCode
Scientific computing in Python
- Nvidia Nemotron 3.5 Lightning: 32.1%
- Nvidia Nemotron 3.5 Super VL: 47.8%Top
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Nvidia Nemotron 3.5 Lightning: 60.3%
- Nvidia Nemotron 3.5 Super VL: 69.0%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 536.8 tok/s
- Faster than 98% of 254 models
- Time to first token
- 0.9 s
- Quicker than 96% of 254 models
- Prompt cache hits
- 84.6%
- About $0.0162 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "nvidia/nemotron-3.5-lightning",
"reasoning_effort": "none",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="nvidia/nemotron-3.5-lightning",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)nvidia
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