NVIDIANVIDIA Nemotron Nano 9B v2
NVIDIA Nemotron Nano 9B v2 is a NVIDIA open-weights reasoning model, released 18 Aug 2025. Its best configuration (thinking reasoning effort) ranks #630 of 785 on the BenchLeader Index at 41.5 ±2.9, in the lower half. The ± is the point: 278 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in knowledge (43) and lowest in instruction following (32). At $0.070 per million tokens blended it is among the cheapest fifth of ranked models. Output speed of 95 tokens per second puts it faster than most, with a first answer in 21.8 s. It has been measured at 3 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 18 Aug 2025.stale: no new result in six months
- Blended price
- $0.070/M
- $0.040 in · $0.160 out
- Output speed
- 95 tok/s
- measured by Artificial Analysis
- First answer
- 22 s
- Context
- 131k
- Full answer
- 27 s
- median, reasoning included
- Cost per run
- –
- Released
- 18 Aug 2025
- Overall index42
- Reasoning41
- Agents & tools35
- Knowledge43
- Instruction following32
- Long context35
- Composite38
Reasoning-effort configurations
The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| no reasoning | 40.6 | #654 | 165 tok/s | 1.04 s | $0.0001 | Agents & tools 34 · Composite 37 · Instruction following 32 · Knowledge 36 · Long context 36 · Reasoning 41 |
| thinkingbest | 41.5 | #630 | 95 tok/s | 22 s | $0.0001 | Agents & tools 35 · Composite 38 · Instruction following 32 · Knowledge 43 · Long context 35 · Reasoning 41 |
| not stated | – | – | – | – | $0.0001 | Reasoning 45 |
How its index has moved
9 Sept 2026 to 21 Oct 2026- thinking
- no reasoning
The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.
Benchmark results
See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | no reasoning | thinking | not stated | Source |
|---|---|---|---|---|
| GPQA Diamond (AA)not in index | 55.7%#403 | 57.0%#397 | – | Artificial Analysis |
| Humanity's Last Exam (AA)not in index | 4.6%#489 | 4.9%#467 | – | Artificial Analysis |
| Kagi LLM Benchmarkeffort not stated | – | – | 47.4%#90 | Kagi LLM Benchmark |
| CritPt | 0.0%#315 | 0.0%#315 | – | Artificial Analysis |
Agents & tools
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| Terminal-Bench Hard | 0.8%#349 | 1.5%#338 | Artificial Analysis |
| τ²-Bench Telecom (AA)not in index | 23.4%#304 | 21.9%#317 | Artificial Analysis |
Knowledge
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA-Omniscience | -57.3#443 | -41.5#328 | Artificial Analysis |
| AA-Omniscience: accuracynot in index | 9.8%#497 | 11.8%#478 | Artificial Analysis |
| AA-Omniscience: non-hallucinationnot in index | 25.6%#239 | 39.5%#161 | Artificial Analysis |
Instruction following
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| IFBench | 27.1%#380 | 27.6%#378 | Artificial Analysis |
Long context
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA-LCR | 24.0%#415 | 22.7%#420 | Artificial Analysis |
Composite
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA Intelligence Index v4.3.2 | 6.8#506 | 7.4#476 | Artificial Analysis |
Price history
The price above, per 1M tokens, every day it changed.
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0001 | – | 24.9 s |
| Summarize a 30-page report | 12,000 / 600 | $0.0006 | – | 28.1 s |
| Code edit | 6,000 / 1,500 | $0.0005 | – | 37.6 s |
| Agentic coding session | 60,000 / 4,000 | $0.0030 | – | 1.1 min |
| Structured extraction | 2,000 / 200 | $0.0001 | – | 23.9 s |
More from NVIDIA
See also
Questions people ask
- What are NVIDIA Nemotron Nano 9B v2's benchmark scores?
- As of 24 Oct 2026, NVIDIA Nemotron Nano 9B v2 (thinking effort) scores 41.5 ±2.9 on the BenchLeader Index, strongest in knowledge (43) and weakest in instruction following (32). That rests on 6 independent benchmark results, and every score on this page links to its publisher.
- How does NVIDIA Nemotron Nano 9B v2 rank?
- NVIDIA Nemotron Nano 9B v2 (thinking effort) is #630 of 785 ranked configurations on 24 Oct 2026. 278 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
- How much does NVIDIA Nemotron Nano 9B v2 cost per 1M tokens?
- As of 24 Oct 2026, NVIDIA Nemotron Nano 9B v2 costs $0.040 per 1M input tokens and $0.160 per 1M output tokens, $0.070 blended (three input tokens per output token). The list price last changed on 6 Oct 2026.
- When was NVIDIA Nemotron Nano 9B v2 released?
- NVIDIA released NVIDIA Nemotron Nano 9B v2 on 18 Aug 2025. BenchLeader has results for it at 3 reasoning-effort settings.
Data as of 24 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “NVIDIA Nemotron Nano 9B v2: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/nemotron-nano-9b-v2.