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ModelCap

Nemotron 3 Ultra

Official publisher releaseLimited evidenceRestricted licenseFree tier6.9d #251 → #252

NVIDIA·#252 of 352 on the current board·cheaper than #226 GPT-4 Turbo

Nemotron 3 Ultra is a language model from NVIDIA. It ranks #252 of 352 on ModelCap's current board, with a thinly supported Index score of 26.7, partly measured on public benchmarks and partly modeled. Its score range of 2.9–50.5 spans positions #129–#352. It is listed at $0.60 per million input tokens and $2.40 per million output tokens across 3 providers. It reads up to 262K tokens of context, and its weights are downloadable under a use-restricted licence.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
26.7#252
Partly measured on public benchmarks and partly modeled · range 2.9–50.5
Evidence as of 4 Nov 2026, 00:00 UTC
Market Gravity
61.0Increased by 0.6
Secondary market signal
Input
$0.60
per 1M tokens
Output
$2.40
per 1M tokens
Context
262K
tokens
Providers
3
5 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp4/flexCheapest$0.40$1.76262Kfp4100.0%
DeepInfrafp4$0.50$2.20262Kfp4100.0%
BaseTenfp4/us$0.60$2.40203Kfp4100.0%
BaseTenfp4$0.60$2.40203Kfp4100.0%
Venicefp8$0.625$3.13256Kfp8100.0%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
deepinfra
live
$1.00$5.00262K1126 ms22.7 tok/stools · structured

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

EffortAgent scoreSource rankSampleSource
Default
Nemotron 3 Ultra
-15.60%
CI -18.9–-12.3%
#54228K obs
14K sessions
LMArena Agent
Match 100%

Reported evaluation leads (7)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.

Dataset / taskMetricValueRevisionProvenance
cais/hle
hle
—26.7
Unpinned
not published
Reported
Not used in launch estimate
cais/hle
hle
—37.4
Unpinned
not published
Reported
Not used in launch estimate
harborframework/terminal-bench-2.1
terminalbench_2_1
—56.4
Unpinned
not published
Reported
Not used in launch estimate
Idavidrein/gpqa
diamond
—87
Unpinned
not published
Reported
Not used in launch estimate
SWE-bench/SWE-bench_Multilingual
swe_bench_multilingual_%_resolved
—67.7
Unpinned
not published
Reported
Not used in launch estimate
SWE-bench/SWE-bench_Verified
swe_bench_%_resolved
—71.9
Unpinned
not published
Reported
Not used in launch estimate
TIGER-Lab/MMLU-Pro
mmlu_pro
—86.8
Unpinned
not published
Reported
Not used in launch estimate

ModelCap Index · Current board

Methodology
26.7
Partly measured on public benchmarks and partly modeled
Current board
#252 of 352

Limited evidence. Measured on only 1 public benchmark, with limited support, so the score is less certain than a broadly measured one. What this label means

Score range
2.9–50.5
Rank range
#129–#352
Evidence as of
4 Nov 2026, 00:00 UTC
Benchmarks used
LMArena Agent
Technical details
Public rank basis
Measured · blended (measured)
Evidence label
Measured · blended · publisher-corpus-prior over 210 held-out anchors (61%); 1 specialist-board observation at 1.8% support (39%); shrunk 15.1 up toward the measured corpus
Index support
1.8% · weak
Identity binding
Exact catalogue product · nvidia/nvidia/nemotron-3-ultra-550b-a55b/bf16 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16@77df655d5e9f8362164ed14dd8b48f8bce657498 (not the evaluation revision)
Index observations used
1
Qualified Index evidence point
26.7
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
26.7 ± 18.6
Independent share
39%
Shrink toward corpus
+15.1
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
publisher-corpus-prior over 210 held-out anchors
36.3 ± 23.861%
Specialist board measurement
1 specialist-board observation at 1.8% support
11.6 ± 29.839%
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
11.6
Evidence status
provisional · 3% mass
General preference
—
Coding
—
Agents & tools
11.6
Reasoning
—
Evidence breadth
5%
Evidence coverage
2%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
53.5
Liquidity (providers × uptime)
85.1
Open reach (HF downloads)
—
Surface (context / tools / modalities)
75.3
Freshness
55.3
  • · OpenRouter popularity #15
  • · 3 live providers
  • · Catalogue: context 262144, reasoning, tools
  • · First seen 2026-06-04

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
80.8
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
92.5
Deployability
100.0
Evaluation provenance
33.8

Not yet published: the base model it derives from, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
61.0
OpenRouter weekly popularity
#15 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
53.5

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
85.1

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
55.3

Time since first public availability, on a six-month half-life.

Specification

Model ID
nvidia/nemotron-3-ultra-550b-a55b
Context window
262K tokens
Declared output cap
183K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.12 / 1M
First seen on OpenRouter
4 Jun 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.

Access
Restricted license
Pinned revision
77df655d5e9f
Parameters
560.5B
Architecture
NemotronHForCausalLM
Model type
nemotron_h
Hugging Face downloads (30d)
1.2M
Downloads (all time)
2.8M
Likes
382
Repository updated
24 Aug 2026, 23:47 UTC

Benchmark leaderboards featuring Nemotron 3 Ultra

All leaderboards
Public benchmark boards on which Nemotron 3 Ultra has a published result
LeaderboardScoreSource rankConfigurationPublished
LMArena Agent leaderboardLMArena-15.6%-18.9%–-12.3%#54 of 58Default4 Nov 2026

Alternatives to Nemotron 3 Ultra, by the numbers

Ranked neighbours

Models within 3 places of #252 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked NVIDIA models

The same publisher's other current models with a public Index position.

Nemotron 3 Ultra: common questions

How does Nemotron 3 Ultra rank among AI models?

Nemotron 3 Ultra holds ModelCap Index position #252 of 352 ranked language models as of 6 November 2026, with an Index score of 26.7 (interval 2.9–50.5); evidence: measured · blended. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Nemotron 3 Ultra cost per 1M tokens?

Nemotron 3 Ultra is listed at $0.60 per 1M input tokens and $2.40 per 1M output tokens as of 6 November 2026; the lowest output price among 3 providers is $1.76 on DeepInfra. Prices come from the OpenRouter catalogue and re-observe on every refresh; at least one provider lists a free tier. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $2.40 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Nemotron 3 Ultra?

Nemotron 3 Ultra has a published context window of 262K tokens (262,144). The snapshot lists a 182,520 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Nemotron 3 Ultra open-weight?

Restricted license (openmdw-1.1). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 on Hugging Face.

Which API providers serve Nemotron 3 Ultra?

3 providers serve Nemotron 3 Ultra through OpenRouter as of 6 November 2026: DeepInfra, BaseTen and Venice. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Nemotron 3 Ultra been evaluated on?

Nemotron 3 Ultra has published results on 1 public board tracked by ModelCap as of 6 November 2026: LMArena Agent -15.6% (#54 of 58). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was Nemotron 3 Ultra released?

Nemotron 3 Ultra first appeared in the catalogue on 4 Jun 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.