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Open weights model

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Released June 2026

Nemotron 3 Ultra 550B A55B: Intelligence, Performance & Price Analysis

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Available providers

Performance

Time to first answer token 4.72sOutput speed 199 tok/s

4.3

Time per Intelligence Index task (minutes)

Cost

In $0.60Out $2.40Cache discount 80%

$2.21

Cost per Intelligence Index task

Verbosity

Input tokens 5.28BOutput/input 1.153%

60.9M

Output tokens from Intelligence Index

Nemotron 3 Ultra 550B A55B (Reasoning) is among the least intelligent models and somewhat expensive when comparing to other open weight models of similar size. It's also notably quick per task and highly concise. The model supports text input, outputs text, and has a 262k tokens context window.

Nemotron 3 Ultra 550B A55B (Reasoning) scores 12 on the Artificial Analysis Intelligence Index, placing it at the lower end among comparable models (median: 23). When evaluating the Intelligence Index, it generated 60.9M tokens, which is very concise in comparison to the median of 104M.

Pricing for Nemotron 3 Ultra 550B A55B (Reasoning) is $0.60 per 1M input tokens (somewhat expensive, median: $0.43) and $2.40 per 1M output tokens (somewhat expensive, median: $1.84). On average, it costs $2.21 per task to evaluate Nemotron 3 Ultra 550B A55B (Reasoning) on the Intelligence Index.

At 4.3 minutes per Intelligence Index task, Nemotron 3 Ultra 550B A55B (Reasoning) is notably quick compared with the median of 14.0 minutes for comparable models (lower is better).

Reasoning	Yes
Input modality	Supports: text
Output modality	Supports: text
Context window	262k ~393 A4 pages of size 12 Arial font
Total parameters	550B
Active parameters	55B Number of parameters active per token during inference
License	OpenMDW
Model weights	Hugging Face

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:

Tiny: ≤4B parameters
Small: 4B–40B parameters
Medium: 40B–150B parameters
Large: >150B parameters

Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

<$0.15 per 1M tokens
$0.15–$1 per 1M tokens
>$1 per 1M tokens

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

No publicly available API

Time per Task

Inference time (minutes) per Intelligence Index task · Lower is better

No publicly available API

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

No publicly available API

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v5.0.1 incorporates 9 evaluations: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), and Terminal-Bench-Science 0.1

Artificial Analysis Intelligence Index v5.0.1 includes: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Capability Indexes

Measures the performance of models on specific capabilities and industries

Finance & Accounting Index

Incorporates 5 evaluations: AA-Briefcase v1.1, AA-Omniscience v1.1, HLE-Diamond, AutomationBench-AA, GDP.pdf · Higher is better

Strategy & Ops Index

Incorporates 4 evaluations: AutomationBench-AA, AA-Briefcase v1.1, AA-Omniscience v1.1, GDP.pdf · Higher is better

Legal Index

Incorporates 5 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf, AutomationBench-AA · Higher is better

Healthcare & Medical Index

Incorporates 5 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, MLCR-AA, AutomationBench-AA, HLE-Diamond · Higher is better

Engineering Index

Incorporates 7 evaluations: AA-Omniscience v1.1, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1, HLE-Diamond, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Briefcase v1.1 · Higher is better

Economics Index

Incorporates 4 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf · Higher is better

Benchmarks

Evaluations

Evaluations measured independently by Artificial Analysis · AA-PersonalityBench scores are percentile ranks from 1 to 100

AA-Briefcase v1.1

Agentic knowledge work, Elo

AA-Omniscience v1.1 AccuracyUpdated

Knowledge

AA-Omniscience v1.1 Non-Hallucination RateUpdated

1 - hallucination rate

AutomationBench-AA

Agentic SaaS workflows

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

FrontierCode-AA 2.0New

Agentic software engineering in open-source repositories

HLE-DiamondNew

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

Terminal-Bench 4.0

Agentic coding & terminal use

CritPt v2 (Hard Subset)

Physics reasoning

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

EnterpriseOps-Gym-AA

Agentic business operations

GDPval-AA v2.1

Agentic real-world work tasks, Elo

AA-3DNew

Agentic interactive 3D experiences, Elo

Code2Video-AANew

Product and brand videos designed in code, Elo

MLCR-AAUpdated

Medical long context reasoning

AA-PersonalityBench: Expressiveness ScoreNew

Rich, varied, well-crafted language

AA-PersonalityBench: Organization ScoreNew

Well-structured, scannable, answer-first

AA-PersonalityBench: Transparency ScoreNew

Truthful, acknowledges uncertainty, non-sycophantic

AA-PersonalityBench: Slop ScoreNew

Use of filler and generic language

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

AA-PersonalityBenchNew

Personality Indexes

Each axis is one of 8 personality indexes: the mean of its traits’ Elo z-scores, percentile ranked from 1 to 100 across all models evaluated in the benchmark

Openness Index

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)

Cost

Cost per Intelligence Index Task

Weighted average cost (USD) per Intelligence Index task · Segmented by token type · Lower is better

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Performance

Measured by time per task (minutes), output speed (tokens per second), time to first answer token and time to first token (seconds)

Time per Intelligence Index Task

Output tokens divided by end-to-end output speed (minutes per Intelligence Index task) · Speed at the model's own endpoint or the median across providers · Lower is better

The weighted average time (minutes) per Artificial Analysis Intelligence Index task: output tokens per task divided by output speed, weighted by each benchmark's weight in the Intelligence Index.

Speed and latency metrics average each endpoint's runs over the past 5 days, and the error rate pools them. We run the benchmark every 6 hours, and endpoints of deprecated models every 18 hours.

Output Speed

Output tokens divided by total request time, including time to first token · Higher is better

Output tokens, including reasoning tokens, received per second over a request's full duration, from sending the request to receiving the final token. The headline value averages each Performance v3 workload over the past 5 days, then averages the workloads.

Time to First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.

Token Use

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

Context Window

Context window: tokens limit · Higher is better

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Model Size (Open Weights Models Only)

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference (billions)

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Further details

								Weights
Nemotron 3 Ultra 550B A55B (Reasoning)	NVIDIA	12	550B 55B active at inference time	262k	$0.44	4.3	199	🤗

Frequently Asked Questions

Common questions about Nemotron 3 Ultra 550B A55B

Nemotron 3 Ultra 550B A55B was released on June 4, 2026.

Nemotron 3 Ultra 550B A55B was created by NVIDIA.

Nemotron 3 Ultra 550B A55B scores 12 on the Artificial Analysis Intelligence Index, placing it at the lower end among other open weight models of similar size (median: 23).

Nemotron 3 Ultra 550B A55B takes 4.3 minutes per Intelligence Index task (based on the median across providers serving the model), which is among the quickest compared to other open weight models of similar size (median: 14.0 minutes; lower is better).

Nemotron 3 Ultra 550B A55B has a time to first answer token of 4.72s (based on the median across providers serving the model), which is very competitive compared to other open weight models of similar size (median: 19.20s).

Nemotron 3 Ultra 550B A55B costs $0.60 per 1M input tokens (somewhat higher than average, median: $0.43) and $2.40 per 1M output tokens (somewhat higher than average, median: $1.84), based on the median across providers serving the model.

Nemotron 3 Ultra 550B A55B costs $0.60 per 1M input tokens and $2.40 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.44 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, Nemotron 3 Ultra 550B A55B generated 60.9M output tokens, which is very competitive compared to other open weight models of similar size (median: 104M).

Yes, Nemotron 3 Ultra 550B A55B is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Nemotron 3 Ultra 550B A55B supports text input.

Nemotron 3 Ultra 550B A55B supports text output.

No, Nemotron 3 Ultra 550B A55B does not support image input. It can only process text.

No, Nemotron 3 Ultra 550B A55B is not multimodal. It only supports text input.

Nemotron 3 Ultra 550B A55B has a context window of 262k tokens. This determines how much text and conversation history the model can process in a single request.

Yes, Nemotron 3 Ultra 550B A55B is open weights. The model weights are publicly available and can be downloaded for self-hosting.

Nemotron 3 Ultra 550B A55B has 550B parameters (55B active).

Nemotron 3 Ultra 550B A55B is a Mixture of Experts (MoE) model with 550B total parameters, but only 55B active parameters are used during inference.

Nemotron 3 Ultra 550B A55B is released under the OpenMDW license. This license allows commercial use. View license

Nemotron 3 Ultra 550B A55B achieves a score of 12 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across knowledge work, coding, science, and general knowledge.

Yes, Nemotron 3 Ultra 550B A55B is available via API through 4 providers. Compare API providers

Nemotron 3 Ultra 550B A55B is available through 4 API providers. Compare providers

Nemotron 3 Ultra 550B A55B: Intelligence, Performance & Price Analysis

Model summary

IntelligenceUpdated

Technical specifications

131 models in this class

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Intelligence Index vs. Cost per Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Capability Indexes

Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

AA-PersonalityBenchNew

Personality Indexes

Openness Index

Artificial Analysis Openness Index: Score

Cost

Cost per Intelligence Index Task

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Cache Hit

Performance

Time per Intelligence Index Task

Time per Intelligence Index Task

Time Period

Output Speed

End-to-End Output Speed

Time to First Answer Token

Time to First Answer Token

Token Use

Output Tokens per Intelligence Index Task

Output Tokens per Intelligence Index Task

Context Window

Context Window

Context Window for RAG

Context Window

Model Size (Open Weights Models Only)

Model Size: Total and Active Parameters

Total Parameters

Active Parameters at Inference Time

Further details

More from NVIDIA

Frequently Asked Questions

When was Nemotron 3 Ultra 550B A55B released?

Who created Nemotron 3 Ultra 550B A55B?

How intelligent is Nemotron 3 Ultra 550B A55B?

How fast is Nemotron 3 Ultra 550B A55B?

What is the latency of Nemotron 3 Ultra 550B A55B?

How much does Nemotron 3 Ultra 550B A55B cost?

What is Nemotron 3 Ultra 550B A55B API pricing?

How verbose is Nemotron 3 Ultra 550B A55B?

Is Nemotron 3 Ultra 550B A55B a reasoning model?

What input modalities does Nemotron 3 Ultra 550B A55B support?

What output modalities does Nemotron 3 Ultra 550B A55B support?

Can Nemotron 3 Ultra 550B A55B process images?

Is Nemotron 3 Ultra 550B A55B multimodal?

What is the context window of Nemotron 3 Ultra 550B A55B?

Is Nemotron 3 Ultra 550B A55B open source?

How many parameters does Nemotron 3 Ultra 550B A55B have?

What are the active parameters of Nemotron 3 Ultra 550B A55B?

What is the license for Nemotron 3 Ultra 550B A55B?

How does Nemotron 3 Ultra 550B A55B perform on benchmarks?

Is Nemotron 3 Ultra 550B A55B available via API?

Where can I use Nemotron 3 Ultra 550B A55B?