Nemotron Nano 9B V2 (free)

Nemotron Nano 9B V2 (free) by NVIDIA excels in the Coding category, where it ranks #83 with a composite score of 54/100. NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so. It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

Nemotron Nano 9B V2 (free) is priced at $0.00 per million input tokens and $0.00 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, Nemotron Nano 9B V2 (free) holds rank #83 out of 6 models tracked. Its quality rank is #83 and adoption rank is #83. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

Nemotron Nano 9B V2 (free) has been evaluated across 6 different signals. Its strongest areas include Capabilities (57/100), Context Window (81/100), Output Capacity (20/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 54/100 reflects a weighted combination of all tracked signals.

Nemotron Nano 9B V2 (free) is available as a free, open-source model. You can run it locally or use it through various hosting providers. Some API providers may charge for hosted inference, so check individual provider pricing.