# NVIDIA Nemotron 3 Ultra 550B A55B NVFP4

NVIDIA Nemotron 3 Ultra 550B A55B NVFP4 is a language model from NVIDIA with a 512K-token context window. Provider list price is $0.60 per million input tokens and $3.60 per million output; on Allocate you pay $0.64 and $3.85 with the 7% transaction fee. It is a closed model served over API; the weights are not published.

## Pricing

| | Provider list | On Allocate |
| --- | --- | --- |
| Input, per M tokens | $0.60 | $0.64 |
| Output, per M tokens | $3.60 | $3.85 |
| Cached input, per M tokens | $0.20 | $0.21 |

Token usage bills at the provider list price plus the 7% transaction fee. Prices checked 2026-07-08.

## Facts

| Field | Value |
| --- | --- |
| Lab | NVIDIA |
| Modality | Language |
| Context window | 512K tokens |
| License | Proprietary API |
| Open weights | No |
| Fine-tunable | No |
| Catalog id | nvidia/nemotron-3-ultra-550b-a55b |

## What a real workload costs

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each: 1,200M input and 350M output tokens. At list prices that is 1,200 × $0.60 + 350 × $3.60 = $1,980 a month. Billed on Allocate it is $2,119 with the 7% transaction fee.

## Common questions

### How much does NVIDIA Nemotron 3 Ultra 550B A55B NVFP4 cost per million tokens?

Provider list price is $0.60 per million input tokens and $3.60 per million output tokens. On Allocate you pay list plus the 7% transaction fee: $0.64 in and $3.85 out.

### What context window does NVIDIA Nemotron 3 Ultra 550B A55B NVFP4 have?

512,288 tokens (512K). At roughly 0.75 words per token, that is about 384k words of English text per request.

### What does cached input cost on NVIDIA Nemotron 3 Ultra 550B A55B NVFP4?

$0.20 per million tokens at list ($0.21 billed). Repeated prompt prefixes, such as a stable system prompt or tool definitions, bill at this rate instead of the full input price.

### Can I fine-tune NVIDIA Nemotron 3 Ultra 550B A55B NVFP4?

No. NVIDIA Nemotron 3 Ultra 550B A55B NVFP4 is a closed model served over API; the weights are not published. If you want a model you can train and own, start from an open-weights base in the catalog and fine-tune that.

### How do I call NVIDIA Nemotron 3 Ultra 550B A55B NVFP4 on Allocate?

Send nvidia/nemotron-3-ultra-550b-a55b in the model field of the OpenAI-compatible endpoint at api.allocate.network/v1, or point a route name (like prod/support-agent) at it so you can swap the model later without a deploy.

---

[HTML page](https://allocate.network/models/nvidia-nemotron-3-ultra-550b-a55b) · [Machine-readable catalog](https://allocate.network/catalog.json)