AI 모델 인텔리전스

Nvidia Nemotron 3.5 Lightning Thinking

nano-gpt/nemotron-3-5-lightning-thinking

제공: nano-gpt · 패밀리: nemotron · 출시 2026-08-11

⚠ 이 모델은 커뮤니티 파인튜닝 / 파생본으로, 벤더 공식 릴리스가 아닙니다.

$0.050
입력 / 1M 토큰
$0.200
출력 / 1M 토큰
1M
컨텍스트 창
66K
최대 출력

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

기능

도구 호출추론구조화 출력첨부오픈 웨이트온도 제어
모달리티: 입력 text · 출력 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding91
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)20/20
  • Provider availability1/10
Agents91
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output100
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume20/20
Cost efficiency82
  • Headline price (log-scaled)77/95
  • Has prompt-cache pricing5/5
Long context90
  • Context window (100K → 2M)80/90
  • Has published price for full window10/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.35
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$0.70
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.20
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$0.60
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$0.72
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

가격 상세

추천 가격 제공자: nano-gpt · nvidia/nemotron-3.5-lightning:thinking

$0.050
입력
$0.200
출력
$0.010
캐시 읽기

1곳 제공사에서 이용 가능

제공자제공자 모델 ID입력 / 1M출력 / 1M컨텍스트출시일
NanoGPT
nano-gpt
nvidia/nemotron-3.5-lightning:thinking$0.050$0.2001M2026-08-11

Frequently asked questions

How much does Nvidia Nemotron 3.5 Lightning Thinking cost?

Nvidia Nemotron 3.5 Lightning Thinking costs $0.050 per 1M input tokens and $0.200 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Nvidia Nemotron 3.5 Lightning Thinking?

Nvidia Nemotron 3.5 Lightning Thinking has a context window of 1M tokens, with a max output of 66K tokens per reply. This is the total combined size of prompt + completion.

Does Nvidia Nemotron 3.5 Lightning Thinking support tool calling?

Yes. Nvidia Nemotron 3.5 Lightning Thinking supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Nvidia Nemotron 3.5 Lightning Thinking support structured output / JSON mode?

Yes. Nvidia Nemotron 3.5 Lightning Thinking supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Nvidia Nemotron 3.5 Lightning Thinking accept image input?

No. Nvidia Nemotron 3.5 Lightning Thinking only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Nvidia Nemotron 3.5 Lightning Thinking open-weight?

Yes. Nvidia Nemotron 3.5 Lightning Thinking's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Nvidia Nemotron 3.5 Lightning Thinking?

If Nvidia Nemotron 3.5 Lightning Thinking doesn't fit, consider ByteDance Seed 2.1 Turbo, Auto model, Claw Low. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More nano-gpt models

마지막 업데이트:

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.