NVIDIA Nemotron Nano 9B v2
nvidia/nemotron-nano-9b-v2제공: NVIDIA · 패밀리: nemotron · 출시 2025-08-18 · 지식 컷오프: 2024-09
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
기능
Model fit scores
0–100 · higher is betterThese 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.
Coding65
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability3/10
Agents68
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit5/15
- Provider availability3/10
JSON / structured output99
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency76
- Headline price (log-scaled)76/95
- Has prompt-cache pricing0/5
Long context46
- Context window (100K → 2M)36/90
- Has published price for full window10/10
Production-readiness73
- Number of independent providers15/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers8/10
- Official model (not derivative)15/15
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.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.41 < $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 | $0.83 < $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 | $0.23 < $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 | $0.71 < $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 | $0.86 < $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: amazon-bedrock · nvidia.nemotron-nano-9b-v2
3곳 제공사에서 이용 가능
| 제공자 | 제공자 모델 ID | 입력 / 1M | 출력 / 1M | 컨텍스트 | 출시일 |
|---|---|---|---|---|---|
| Amazon Bedrock amazon-bedrock | nvidia.nemotron-nano-9b-v2 | $0.060 | $0.230 | 131K | 2025-08-18 |
| Vercel AI Gateway vercel | nvidia/nemotron-nano-9b-v2 | $0.060 | $0.230 | 131K | 2025-08-18 |
| Merge Gateway merge-gateway | nvidia/nemotron-nano-9b-v2 | $0.060 | $0.230 | 128K | 2025-08-18 |
제공자 간 데이터 불일치
- context_window varies: 128000, 131072
제공자별로 이 모델의 값이 다릅니다. 위의 핵심 정보는 대표 제공자 기준이며, 제공자별 상세는 표를 참고하세요.
Frequently asked questions
How much does NVIDIA Nemotron Nano 9B v2 cost?
NVIDIA Nemotron Nano 9B v2 costs $0.060 per 1M input tokens and $0.230 per 1M output tokens, sourced from amazon-bedrock. 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 Nano 9B v2?
NVIDIA Nemotron Nano 9B v2 has a context window of 131K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does NVIDIA Nemotron Nano 9B v2 support tool calling?
Yes. NVIDIA Nemotron Nano 9B v2 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 Nano 9B v2 support structured output / JSON mode?
Yes. NVIDIA Nemotron Nano 9B v2 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 Nano 9B v2 accept image input?
No. NVIDIA Nemotron Nano 9B v2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is NVIDIA Nemotron Nano 9B v2 open-weight?
Yes. NVIDIA Nemotron Nano 9B v2'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 Nano 9B v2?
If NVIDIA Nemotron Nano 9B v2 doesn't fit, consider Nemotron 3 Ultra 550B A55B, Nemotron 3 Nano 30B A3B, Nemotron 3 Super 120B A12B. 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.
Explore more
More NVIDIA models
- Nemotron 3 Ultra 550B A55B$0.40 in / $1.76 out
- Nemotron 3 Nano 30B A3B$0.05 in / $0.20 out
- Nemotron 3 Super 120B A12B$0.05 in / $0.25 out
- Nemotron 3.5 Super VL$0.06 in / $0.35 out
- Nemotron 3.5 Lightning 30B A3B$0.05 in / $0.15 out
Capability lists this model is in
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.