Nemotron 3 Ultra
v20260604NVIDIA
NVIDIA's open frontier reasoning model, released 2026-06-04 to complete the Nemotron 3 rollout (Nano Dec 2025, Super Mar 2026): a 550B total / 55B active LatentMoE hybrid Mamba-Transformer under OpenMDW-1.1 with open weights, training data, and recipes. 1M-token context, 71.9% SWE-bench Verified (vendor), Artificial Analysis Index 48 — the top-scoring US open-weight model — with ~140 tok/s decode and the best non-hallucination score in its comparison set (78.7 AA-Omniscience).
Trust Vector Analysis
Dimension Breakdown
🚀Performance & Reliability+
Strongest US open-weight model on the Artificial Analysis Intelligence Index (48, #9 overall) with class-leading decode speed (~140 tok/s) and a 1M-token context. Vendor benchmark peaks (SWE-bench 71.9) run a few points above independent multi-harness reproductions (65.0-70.4). Verbosity (~2.3x peer output tokens) is the main efficiency caveat.
Vendor coding benchmarks cross-checked against independent multi-harness SWE-bench reproductions
Independent aggregate intelligence index plus vendor reasoning benchmarks; some vendor numbers await third-party replication
Knowledge and long-context retrieval benchmarks from launch materials, corroborated by independent press analysis
Cross-harness benchmark variance and community reports; only one month of production usage available
Independent hosted-endpoint speed measurements plus vendor throughput comparisons
Qualitative assessment from early independent benchmarking; p95 distributions not yet published one month post-launch
Official specification from model card; note that individual API providers may cap served context
Multi-provider availability assessment; only one month of hosted operating history
🛡️Security+
Reasonable default safety stack including a dedicated companion content-safety model, but almost no independent red-team literature exists yet given the June 2026 launch. Open weights shift guardrail responsibility to deployers who fine-tune.
Review of vendor safety documentation; independent OWASP LLM01 testing not yet available for this release
Assessment of vendor guardrail stack; accounts for open-weight modifiability and absence of independent adversarial evaluations
Analysis of deployment options: self-hosting gives full data isolation, hosted routes depend on provider policies
Review of default-weight safety behavior and the vendor's companion moderation stack
Review of API security features on NVIDIA NIM and principal third-party hosts
🔒Privacy & Compliance+
US-jurisdiction provider with unusually flexible residency thanks to open weights and 25+ hosts, including hyperscaler routes (SageMaker JumpStart) that carry their own certifications. No model-level HIPAA/FedRAMP; regulated buyers should deploy via certified infrastructure.
Review of hosting options and open-weight licensing; residency is fully controllable via self-hosting
Analysis of NVIDIA hosted-service terms plus the self-hosting option
Review of hosted-platform retention policies across the deployment spectrum
Review of data protection capabilities and deployer responsibilities
Verification of provider infrastructure certifications versus model-service-level compliance
Review of data handling across NVIDIA NIM, third-party hosts, and self-hosting
👁️Trust & Transparency+
Transparency is this release's standout: weights, 20T-token training data, and recipes are all published under OpenMDW-1.1 — materially beyond typical open-weight disclosure. Independent bias and calibration audits are still pending one month post-launch.
Evaluation of reasoning-trace accessibility and weight/recipe inspectability
Non-hallucination benchmark results from launch materials, pending broader independent replication
Review of vendor responsible-AI disclosures; third-party fairness evaluations pending given launch recency
Qualitative assessment of confidence expression in outputs
Review of model card and technical documentation completeness
Review of published training datasets and recipes; best-in-class disclosure among frontier-scale models
Analysis of built-in safety mechanisms in default weights and companion tooling
⚙️Operational Excellence+
Strong launch operations: day-zero support across 25+ hosts and all major inference frameworks, plus a single NVFP4 checkpoint spanning Ampere to Blackwell. Ecosystem and monitoring scores held conservative pending more production history; OpenMDW-1.1 is permissive but newer than Apache 2.0.
Review of API design and feature completeness across NIM and principal hosts
Review of inference-framework support and deployment tooling at launch
Review of release cadence, family roadmap execution, and weight-availability guarantees
Review of monitoring tools across deployment options
Assessment of enterprise support tiers, documentation, and community responsiveness
Analysis of derivative models, third-party hosting breadth, and tooling integrations; scored conservatively given launch recency
Review of licensing terms and restrictions
- +Top-scoring US open-weight model: Artificial Analysis Intelligence Index 48 (#9 of 89)
- +Radical transparency: weights, 20T-token training data, and recipes all released under OpenMDW-1.1
- +1M-token context with RULER 94.7 at full length
- +Fast for its class: ~140 tok/s decode, 1.33s TTFT; vendor-reported 4.8-5.9x throughput vs open peers
- +Best non-hallucination score in its comparison set (78.7 AA-Omniscience)
- +Single NVFP4 checkpoint runs across Ampere, Hopper, and Blackwell; day-zero vLLM/SGLang/TRT-LLM support
- +Completes a predictable family ladder (Nano 30B-A3B, Super 120B-A12B, Ultra 550B-A55B)
- !Very verbose: ~2.3x more output tokens than peers, inflating cost and end-to-end latency on reasoning tasks
- !Trails the open-weight leader Kimi K2.6 by 6 Intelligence Index points (48 vs 54)
- !Vendor benchmark peaks exceed independent reproductions (SWE-bench 71.9 vendor vs 65.0-70.4 across harnesses)
- !Text-only: no image, audio, or video input
- !Launched 2026-06-04: minimal independent red-teaming, bias audits, or production track record
- !550B total parameters require serious multi-GPU infrastructure to self-host
- !OpenMDW-1.1 license is permissive but less familiar to enterprise legal teams than Apache 2.0
Use Case Ratings
code generation
71.9% SWE-bench Verified (vendor; 65.0-70.4 independent) with fast decode suits agentic coding; verbosity raises per-task output cost.
customer support
Capable but text-only, verbose, and primarily English-optimized; oversized for most support tiers.
content creation
Solid structured writing; reasoning verbosity requires prompt discipline for concise content.
data analysis
1M-token context with RULER 94.7 handles very large datasets and logs; text-only, so charts/images need preprocessing.
research assistant
1M context plus the best non-hallucination score in its set (78.7 AA-Omniscience) suits long-document research and long-running agents.
legal compliance
Compliance is deployment-dependent: viable via certified hosts (e.g., SageMaker) or self-hosting; no model-service certifications.
healthcare
No HIPAA path on NVIDIA-hosted endpoints; deploy in compliant infrastructure via open weights.
financial analysis
Strong reasoning and long-context document processing; independent calibration data still limited.
education
Clear reasoning traces aid tutoring, but verbosity and English-first coverage limit fit versus multilingual alternatives.
creative writing
Reasoning-optimized rather than prose-optimized; competent but not distinctive creative output.