Nemotron 3.5 Super VL
nvidia/nemotron-3-5-super-vlPar NVIDIA · famille: nemotron · sorti 2026-10-15
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacités
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.
Coding96
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)20/20
- Provider availability6/10
Agents96
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability6/10
JSON / structured output99
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency75
- Headline price (log-scaled)70/95
- Has prompt-cache pricing5/5
Long context91
- Context window (100K → 2M)81/90
- Has published price for full window10/10
Vision96
- Accepts image input50/50
- Context window (10K → 1M)30/30
- Has published price10/10
- Provider availability6/10
Production-readiness86
- Number of independent providers30/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- 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 | $0.70 < $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 | $1.40 < $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 | $0.40 < $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 | $1.20 < $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 | $1.44 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Détail des tarifs
Tarif recommandé de kilo · nvidia/nemotron-3.5-super-vl
Disponible chez 6 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| OpenRouter openrouter | nvidia/nemotron-3.5-super-vl | $0.150 | $0.500 | 1.05M | 2026-10-15 |
| Vercel AI Gateway vercel | nvidia/nemotron-3.5-super-vl | $0.200 | $0.500 | 1.05M | 2026-10-15 |
| NanoGPT nano-gpt | nvidia/nemotron-3.5-super-vl | $0.150 | $0.500 | 262K | 2026-10-15 |
| Kilo Gateway kilo | nvidia/nemotron-3.5-super-vl | $0.100 | $0.400 | 262K | 2026-10-15 |
| Nebius Token Factory nebius | nvidia/Nemotron-3.5-Super-VL | $0.300 | $0.900 | 1.05M | 2026-10-15 |
| DigitalOcean digitalocean | nemotron-3.5-super-vl | $0.300 | $0.650 | 1.05M | 2026-10-15 |
Incohérences de données entre fournisseurs
- context_window varies: 1048576, 262144
- modalities varies across offerings
Les fournisseurs rapportent des valeurs différentes pour ce modèle. Les infos clés ci-dessus utilisent un fournisseur représentatif ; voir le tableau pour le détail par fournisseur.
Frequently asked questions
How much does Nemotron 3.5 Super VL cost?
Nemotron 3.5 Super VL costs $0.100 per 1M input tokens and $0.400 per 1M output tokens, sourced from kilo. 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 3.5 Super VL?
Nemotron 3.5 Super VL has a context window of 1.05M tokens, with a max output of 236K tokens per reply. This is the total combined size of prompt + completion.
Does Nemotron 3.5 Super VL support tool calling?
Yes. Nemotron 3.5 Super 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 3.5 Super VL support structured output / JSON mode?
Yes. Nemotron 3.5 Super VL 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 Nemotron 3.5 Super VL accept image input?
Yes. Nemotron 3.5 Super VL accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check NVIDIA's docs for the exact rule.
Is Nemotron 3.5 Super VL open-weight?
Yes. Nemotron 3.5 Super 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 3.5 Super VL?
If Nemotron 3.5 Super VL doesn't fit, consider nemotron-3-nano-30b-a3b, Nemotron 3 Ultra 550B A55B, 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-nano-30b-a3b$0.05 in / $0.20 out
- Nemotron 3 Ultra 550B A55B$0.50 in / $2.50 out
- Nemotron 3 Super 120B A12B$0.05 in / $0.25 out
- Nemotron 3.5 Lightning 30B A3B$0.03 in / $0.12 out
- Nemotron 3.5 Content Safety$0.05 in / $0.15 out
Capability lists this model is in
Dernière mise à jour :
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.