Nemotron Nano 9B v2
by NVIDIA · United StatesA Mamba-Transformer hybrid with a reasoning budget you can cap per request.
Specification
The numbers
- Maker
- NVIDIA
- Released
- 2025-08
- Parameters
- 9B
- Architecture
- Hybrid Mamba
- Context window
- 131,072 tokens
- Max output
- 32,768 tokens
- Input
- Text
- Output
- Text
- Reasoning
- Yes
- Tool calling
- Yes
- Knowledge cutoff
- Not reported
- Licence
- NVIDIA Open Model
- Availability
- Not reported
- Weights
- Downloadable
Cost
Price per million tokens
- Input
- $0.04 / M tokens
- Output
- $0.16 / M tokens
- Blended 3:1
- $0.070
This model has open weights, so there is no first-party price. The figures above are a representative third-party hosting rate — you can also run it yourself for the cost of the hardware.
Published scores
Benchmarks
Figures published by NVIDIA or taken from a public leaderboard. Row last checked 2026-08.
| Category | Score | Rank |
|---|---|---|
| ReasoningGPQA Diamond | 64.0% | 51 of 83 reporting the same tests |
| MathsAIME 2025 | 72.1% | 47 of 56 reporting the same tests |
| CodingWriting and repairing real code | Not reported | — |
| KnowledgeBreadth of factual recall under exam conditions | Not reported | — |
| MultimodalReading charts, diagrams and photographs | Not reported | — |
| Instruction followingObeying an exact, checkable format | Not reported | — |
| Human preferenceWhich answer people pick, blind | Not reported | — |
A category averages every benchmark in it that Nemotron Nano 9B v2 reports. The rank counts only models that report the same tests, so it never compares an average over three benchmarks against an average over one.
Every reported test
| MMLU-ProKnowledge | Not reported | No figure published |
|---|---|---|
| GPQA DiamondReasoning | Rank 51 of 83 models reporting | |
| AIME 2025Maths | Rank 47 of 56 models reporting | |
| MATH-500Maths | Not reported | No figure published |
| SWE-bench VerifiedCoding | Not reported | No figure published |
| SWE-bench ProCoding | Not reported | No figure published |
| Terminal-Bench 2.1Coding | Not reported | No figure published |
| Frontier-Bench v0.1Reasoning | Not reported | No figure published |
| Terminal-Bench 4.0Coding | Not reported | No figure published |
| LiveCodeBenchCoding | Not reported | No figure published |
| HumanEvalCoding | Not reported | No figure published |
| MMMUMultimodal | Not reported | No figure published |
| IFEvalInstruction following | Not reported | No figure published |
| LMArena EloHuman preference | Not reported | No figure published |
Where these numbers come from
Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.
A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.
Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.
Same maker
Other models from NVIDIA
| Llama-3.1-Nemotron-Ultra-253BNVIDIA | NVIDIA | 131K | $0.60 | $1.80 | — | 76% | 80.1% | — | NVIDIA Open Model |
| Llama-3.3-Nemotron-Super-49BNVIDIA | NVIDIA | 131K | $0.13 | $0.40 | — | 66.7% | 67.5% | — | NVIDIA Open Model |