Nemotron 3 Nano Omni 30B A3B
NVIDIA · Open Weight · rank 168 · bench-align-v5
Self-hostedCanonical idnemotron-3-nano-omni-30b-a3b
Access typeOpen Weight
Blended $/1MUnavailable75% input / 25% output
Capability shape
Seven axes from the ranking source. A missing axis is drawn as a gap.
Runtime service evidence
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: Observed
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | 7.25 s | 2026-09-17 | 2026-09-17 | |
| Throughput | 327 tok/s | 2026-09-17 | 2026-09-17 |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Endpoint and price matrix
Every published price component, including cache reads and writes.
Self-hosted listingOpen-weight model. Self-hosted or third-party hosted costs vary by provider and infrastructure.No hosted token rate was published for this model, so its per-token price is unavailable rather than zero.
Workload-aware monthly cost example
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
Modelled monthly costUnavailableThe applicable input rate is unavailable.
Modelled tokensUnavailable
Open the simulatorChange this workload
Benchmark record
29 matched benchmark rows with their published value, unit, and provenance.
Knowledge
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| GPQA Graduate-Level Google-Proof Q&A | 72.2 | 448 questions | Graduate level | GPQA: A Graduate-Level Google-Proof Q&A Benchmark |
| GPQA-D GPQA Diamond | 72.2 | Graduate-level science questions | Graduate level | Trinity-Large-Thinking: Scaling an Open Source Frontier Agent |
| MMLU-Pro Massive Multitask Language Understanding Professional | 77.3 | Multiple subjects | Professional level | MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark |
| Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index | 10.3 | Cross-benchmark intelligence index | Display-only external reference | Artificial Analysis |
| AA-GPQA Diamond Artificial Analysis GPQA Diamond | 46.9 | Graduate-level science questions | Graduate-level science reasoning | Artificial Analysis GPQA Diamond Benchmark Leaderboard |
| AA-HLE Artificial Analysis Humanity's Last Exam | 4.8 | Expert-level questions | Frontier expert reasoning | Artificial Analysis Humanity's Last Exam Benchmark Leaderboard |
| AA-Omniscience Index Artificial Analysis Omniscience Index | -57.4 | Knowledge questions | Broad factual knowledge | AA-Omniscience: Knowledge and Hallucination Benchmark |
| AA-Omniscience Accuracy Artificial Analysis Omniscience Accuracy | 15.2 | Knowledge questions | Broad knowledge | Artificial Analysis model benchmarks |
| AA-Omniscience Hallucination Rate Artificial Analysis Omniscience Hallucination Rate | 85.7 | Knowledge questions | Factuality | Artificial Analysis model benchmarks |
Coding
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| LiveCodeBench v5 LiveCodeBench v5 | 63.2 | July 2024 to May 2025 release window | Competitive programming level | LiveCodeBench official repository and release documentation |
| SciCode Scientific Code Benchmark | 32 | — | — | BenchLM |
| AA Coding Index Artificial Analysis Coding Index | 13.8 | Cross-benchmark coding index | Display-only external reference | Artificial Analysis model leaderboards |
Mathematics
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AIME 2025 American Invitational Mathematics Examination 2025 | 82.1 | 15 problems | High school olympiad level | American Invitational Mathematics Examination |
Reasoning
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-LCR Artificial Analysis Long Context Reasoning | 39.7 | Long-context reasoning tasks | Long-context reasoning | Artificial Analysis model benchmarks |
| CritPt Critical Physics Tasks | 0.0 | Research-level physics questions | Research-level physics reasoning | CritPt Benchmark Leaderboard |
Instruction Following
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| IFBench Instruction Following Benchmark | 74.2 | — | — | BenchLM |
| AA-IFBench Artificial Analysis IFBench | 63.2 | Verifiable instruction constraints | Instruction precision | Artificial Analysis IFBench Benchmark Leaderboard |
Agentic
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| GDPval-AA GDPval-AA | 416 | Agentic real-world work tasks | Professional agentic workflows | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA normalized | 0.0 | Economically valuable tasks | Professional agentic workflows | Artificial Analysis model benchmarks |
| OSWorld OSWorld | 47.4 | Computer-use tasks | Broad computer-use suite | GLM-5V-Turbo |
| τ²-bench results τ²-Bench Tool-Agent-User Evaluation | 45.3 | Airline, retail, and telecom customer-service task sets | Dual-control customer-service workflows | τ²-Bench: Evaluating Conversational Agents in a Dual-Control Environment |
Multimodal & Grounded
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| MMMU Massive Multi-discipline Multimodal Understanding | 70.8 | Multimodal academic reasoning | Frontier multimodal | MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI |
| AA-MMMU-Pro Artificial Analysis MMMU-Pro | 53.2 | Multimodal academic reasoning | Frontier multimodal | Artificial Analysis MMMU-Pro Benchmark Leaderboard |
| Video-MME (w/o subtitle) Video-MME without subtitle | 72.2 | Video understanding | Multimodal video reasoning | Qwen3.6 launch benchmarks |
| MMLongBench-Doc MMLongBench-Doc | 57.5 | Long document understanding | Long-context document reasoning | Qwen3.6 launch benchmarks |
| AI2D_TEST AI2D test split | 88.5 | Diagram understanding | Structured visual reasoning | Qwen3.6 launch benchmarks |
| RefCOCO (avg) RefCOCO average | 90.5 | Referring-expression grounding | Fine-grained visual grounding | RefCOCO referring expression datasets |
| ScreenSpot Pro ScreenSpot Pro | 57.8 | 1,581 grounding instructions | Professional GUI grounding | ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use |
| CharXiv CharXiv Reasoning | 76.25 | Scientific chart reasoning | Scientific visualization reasoning | CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs |
Lifecycle and limitations log
Lifecycle events the source associates with this model, plus what this profile does not claim.
No lifecycle event references this model.
That is not evidence the model has no lifecycle plan — only that this source published none.
What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-09-17 17:17 UTC.