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NVIDIANVIDIA Nemotron 3.5 Lightning
NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.
Plain-English overview
What NVIDIA Nemotron 3.5 Lightning actually is
Nemotron 3.5 Lightning has 30 billion total parameters but activates about three billion for each token. NVIDIA designed it as a fast workhorse for specialized tasks inside larger agent systems, while retaining a context window of up to one million tokens.
The preview is available as downloadable weights and across NVIDIA, OpenRouter, and partner infrastructure. Its smaller active footprint makes controlled deployments more approachable than Ultra, although long context and concurrency can still dominate memory use.
Good fit for
- High-volume agent sub-tasks
- Efficient self-hosted reasoning
- Long-context RAG and instruction workflows
Category comparison
The facts that matter for text models
These are provider-published specifications, not Cody benchmark scores. Follow the linked sources for current limits and endpoint-specific exceptions.
- Context window
- Up to 1M tokensMaximum combined prompt and working context documented by the provider.
- Maximum output
- Not separately publishedProvider-published response limit, where available.
- Knowledge cutoff
- Pretraining through Sep 2025; post-training through May 2026Latest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff.
- Input price
- Free prototype or deployment costCurrent standard list price per million input tokens unless noted.
- Output price
- Free prototype or deployment costCurrent standard list price per million output tokens unless noted.
- Inputs
- TextMedia types accepted by the listed model endpoint.
- Tools & agents
- Agentic tools and long-running workflowsSelected native tools and agent-building capabilities, not an exhaustive list.
Pricing & comparisons
Estimate your cost
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Advanced options
NVIDIA Nemotron 3.5 Lightning
NVIDIA
Estimated total (USD)
For the usage above · USD · API pricing, not a subscription
How this estimate works
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
API and provider access
Where to get NVIDIA Nemotron 3.5 Lightning
Availability
Regions and access stage
Available on NVIDIA build, Hugging Face, ModelScope, OpenRouter, NVIDIA NIM, and cloud or inference partners.
The model card describes global deployment; the actual processing region depends on the selected provider or self-hosted infrastructure.
Check live availabilityData and training
The route matters.
Self-hosted weights keep request data under the operator's controls. NVIDIA API trials, OpenRouter, and cloud partners each apply separate logging, retention, and training-use policies.
This is a concise reading of the cited provider material, not legal advice. A third-party gateway can have different storage, routing, training, and residency terms from the model maker's direct API.
Read the provider policyFrequently asked questions
NVIDIA Nemotron 3.5 Lightning FAQ
What is NVIDIA Nemotron 3.5 Lightning?
NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows. Nemotron 3.5 Lightning has 30 billion total parameters but activates about three billion for each token. NVIDIA designed it as a fast workhorse for specialized tasks inside larger agent systems, while retaining a context window of up to one million tokens.
When was NVIDIA Nemotron 3.5 Lightning released?
NVIDIA Nemotron 3.5 Lightning was released on August 11, 2026 according to the cited provider materials.
Where can I access NVIDIA Nemotron 3.5 Lightning?
Available on NVIDIA build, Hugging Face, ModelScope, OpenRouter, NVIDIA NIM, and cloud or inference partners. The access routes listed in this guide are NVIDIA NIM and NVIDIA.
How much does NVIDIA Nemotron 3.5 Lightning cost?
Free NVIDIA prototype endpoint; production and self-host cost varies. The preview is available as downloadable weights and through NVIDIA and partner routes. Hardware, NIM, and provider pricing are separate.
Where is NVIDIA Nemotron 3.5 Lightning available?
Available on NVIDIA build, Hugging Face, ModelScope, OpenRouter, NVIDIA NIM, and cloud or inference partners. The model card describes global deployment; the actual processing region depends on the selected provider or self-hosted infrastructure.
Is my NVIDIA Nemotron 3.5 Lightning API data used for training?
Self-hosted weights keep request data under the operator's controls. NVIDIA API trials, OpenRouter, and cloud partners each apply separate logging, retention, and training-use policies. The policy belongs to the provider route and account terms, so verify it again before production use.
Price comparison
USD per million tokens for the shown API routes at standard context length. Cache and long-context rates may differ. Models without matching reviewed prices are omitted; lower cost does not mean better quality.
- Mistral Small 4$0.15
Mistral AI
- Gemini 3.8 Flash$0.75
Google
- GPT-5.6 Sol$4.00
OpenAI
- GPT-6 Astra$10.00
OpenAI
- Claude Fable 5.1$10.00
Anthropic
- Mistral Small 4$0.60
Mistral AI
- Gemini 3.8 Flash$3.75
Google
- GPT-5.6 Sol$20.00
OpenAI
- GPT-6 Astra$50.00
OpenAI
- Claude Fable 5.1$50.00
Anthropic
Related comparisons
Head-to-head comparisons
NVIDIA Nemotron 3.5 Lightning vs GPT-6 Astra
OpenAI's most capable model for difficult end-to-end work, combining frontier reasoning with a million-token context window and a broad set of agent tools.
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Anthropic's frontier model for ambitious, long-running agentic and coding work, with strong vision and enterprise marketplace availability.
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Google's stable, high-efficiency multimodal model for agents, software work, and large mixed-media inputs at an introductory Flash-tier price.
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SpaceXAI's frontier text-and-image model for coding, agentic tasks, and knowledge work, with direct web, X, and code tools.
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A specialist Grok model that sends several AI agents to investigate a difficult question in parallel, then combines their work into one researched answer.
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Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows.
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Mistral's open-weight frontier model for demanding multimodal, coding, reasoning, and agent workflows, with a 256K context window.
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Mistral's lower-cost open model that combines normal instruction following, reasoning, coding, vision, and agent tools in one endpoint.
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Alibaba's frontier Qwen model for long-context reasoning, coding, tools, and understanding text, images, and video.
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MiniMax's million-token multimodal model for coding, agents, computer use, and long projects at a low direct API price.
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Z.ai's open-weight long-context reasoning model for coding, tools, and agentic work across self-hosted and managed routes.
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Moonshot AI's frontier multimodal model for million-token coding, reasoning, knowledge work, and tool-driven agents.
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TII's compact open reasoning model for text tasks, long contexts, and self-hosted function-calling workflows.
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TII's 34B open instruction model for multilingual text, coding, and controlled self-hosted applications.
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Meta's latest multimodal reasoning model for long-running agents, coding, tools, and complex user collaboration.
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Celeris' agent-focused diffusion language model for fast reasoning, tool loops, structured actions, and OpenAI-compatible integration.
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NVIDIA's largest Nemotron 3 reasoning model for complex agents, coding, planning, tools, RAG, and million-token analysis.
Open full comparisonNVIDIA Nemotron 3.5 Lightning vs Qwen3.8-Flash
Alibaba's efficient million-context multimodal model for fast agents, coding, document work, vision, video understanding, and tool use.
Open full comparisonNVIDIA Nemotron 3.5 Lightning vs DeepSeek-V4-Pro
DeepSeek's flagship million-context text model for difficult reasoning, coding, long-running agents, tools, and very large outputs.
Open full comparisonNVIDIA Nemotron 3.5 Lightning vs DeepSeek-V4-Flash
DeepSeek's lower-cost V4 model for high-volume reasoning, coding, agents, and million-token text workloads.
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