# Nemotron 3.5 Lightning:thinking API

NVIDIA's Nemotron 3.5 Lightning:thinking, through an OpenAI-compatible API. Providers quote it on an open exchange, and each request goes to the offer with the lowest estimated charge that meets your rules.

- Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses.
- The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send nemotron-3.5-lightning:thinking as the model.
- Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request.

## Facts

- Model name: nemotron-3.5-lightning:thinking
- Maker: NVIDIA
- Context window: 1M tokens
- Input price: $0.050 per million tokens
- Output price: $0.200 per million tokens
- Providers: 1 independent provider
- Regions: us

## Providers

- [Architect](https://liquidinference.ai/providers/805445a7-0e40-4c1b-9baf-7b3b01e30e42.md): us, $0.050 input and $0.200 output per million tokens, $0.010 cache read per million tokens, 1M tokens of context

## Request

```sh
curl https://router.inference.ai.exchange/v1/chat/completions \
  -H "Authorization: Bearer $LIQUID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nemotron-3.5-lightning:thinking",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is Nemotron 3.5 Lightning:thinking?

Nemotron 3.5 Lightning:thinking is a model from NVIDIA.

### How much does Nemotron 3.5 Lightning:thinking cost?

Offers now ask $0.050 per million input tokens and $0.200 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer.

### What is the context length of Nemotron 3.5 Lightning:thinking?

The largest offer takes 1,000,000 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can Nemotron 3.5 Lightning:thinking do?

Its providers list Reasoning effort, JSON object, JSON schema, Frequency penalty, Logit bias, Log probabilities, Min-p sampling, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools.

### What inputs and outputs does Nemotron 3.5 Lightning:thinking support?

Text → Text.

### Which providers serve Nemotron 3.5 Lightning:thinking?

1 independent provider quote it now, with 1 offer. The table above ranks them by the cost of a typical job.

### How do I call Nemotron 3.5 Lightning:thinking?

Send "nemotron-3.5-lightning:thinking" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was Nemotron 3.5 Lightning:thinking listed?

The exchange first listed it on 10/10/2026. This is not its release date.

## Related pages

- [This page in a browser](https://liquidinference.ai/models/nemotron-3.5-lightning%3Athinking)
- [Nemotron 3.5 Lightning](https://liquidinference.ai/models/nemotron-3.5-lightning.md)
- [Nemotron 3 Ultra 550B a55b](https://liquidinference.ai/models/nemotron-3-ultra-550b-a55b.md)
- [Llama 3.3 Nemotron Super 49B V1](https://liquidinference.ai/models/llama-3.3-nemotron-super-49b-v1.md)
- [Nemotron 3.5 Content Safety](https://liquidinference.ai/models/nemotron-3.5-content-safety.md)
- [Nemotron: Nano 9B V2](https://liquidinference.ai/models/nemotron-nano-9b-v2.md)
- [Nemotron 3 Nano 30B a3b](https://liquidinference.ai/models/nemotron-3-nano-30b-a3b.md)
- [Set up a client](https://liquidinference.ai/connect/nemotron-3.5-lightning%3Athinking)
- [All models](https://liquidinference.ai/models)
- [Providers](https://liquidinference.ai/providers.md)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)