Nemotron Nano 12B v2 VL
digitalocean/nemotron-nano-12b-v2-vl出品方： digitalocean · 系列: nemotron · 發布 2025-12-01 · 知識截止: 2024-10
⚠ 本模型為社群微調 / 衍生版本，並非廠商官方發布。
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清單
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.
Coding53
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)2/20
- Provider availability1/10
Agents61
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit10/15
- Provider availability1/10
JSON / structured output48
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume18/20
Cost efficiency65
- Headline price (log-scaled)65/95
- Has prompt-cache pricing0/5
Long context45
- Context window (100K → 2M)35/90
- Has published price for full window10/10
Vision78
- Accepts image input50/50
- Context window (10K → 1M)17/30
- Has published price10/10
- Provider availability1/10
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.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $1.30 < $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 | $2.60 < $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 | $0.70 < $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 | $2.20 < $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 | $2.76 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
定價詳情
推薦定價來自 digitalocean · nemotron-nano-12b-v2-vl
於 1 家供應商可用
| 服務商 | 服務商模型 ID | 輸入 / 1M | 輸出 / 1M | 上下文 | 發布日期 |
|---|---|---|---|---|---|
| DigitalOcean digitalocean | nemotron-nano-12b-v2-vl | $0.200 | $0.600 | 128K | 2025-12-01 |
Frequently asked questions
How much does Nemotron Nano 12B v2 VL cost?
Nemotron Nano 12B v2 VL costs $0.200 per 1M input tokens and $0.600 per 1M output tokens, sourced from digitalocean. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Nemotron Nano 12B v2 VL?
Nemotron Nano 12B v2 VL has a context window of 128K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does Nemotron Nano 12B v2 VL support tool calling?
Yes. Nemotron Nano 12B v2 VL 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 Nemotron Nano 12B v2 VL support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Nemotron Nano 12B v2 VL in our data source. Verify with digitalocean's official documentation before relying on it in production.
Can Nemotron Nano 12B v2 VL accept image input?
Yes. Nemotron Nano 12B v2 VL accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check digitalocean's docs for the exact rule.
Is Nemotron Nano 12B v2 VL open-weight?
Yes. Nemotron Nano 12B v2 VL'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 Nemotron Nano 12B v2 VL?
If Nemotron Nano 12B v2 VL doesn't fit, consider Multi-QA-mpnet-base-dot-v1, Wan2.2-T2V-A14B, E5 Large v2. 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 come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More digitalocean models
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- E5 Large v2$0.02 in / $0.00 out
- Stable Diffusion 3.5 Large$0.08 in / $0.00 out
- GTE Large (v1.5)$0.09 in / $0.00 out
Capability lists this model is in
最近更新：
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.