Bedrock
100.00%Context131.1K
Max output131.1K
p50 latency156 ms
Throughput143.0 t/s
Input price$0.06
Output price$0.23
Zero retentionNo training
Model directory
Baseer model profileLanguage model
nvidia/nemotron-nano-9b-v2
Nvidia Nemotron Nano 9B V2
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.\
Input / 1M tokens$0.04
Output / 1M tokens$0.16
Maximum context131.1K
Inference providers2
Price comparison
USD per one million tokens, using current provider data.
Provider latency
Last-hour p50 in milliseconds; lower is better.
Provider uptime
Reported availability over the last 24 hours; not a contractual SLA.
Inference providers
Compare current pricing, performance, and privacy across every available provider.
Deepinfra
100.00%Context131.1K
Max output131.1K
p50 latency262 ms
Throughput96.0 t/s
Input price$0.04
Output price$0.16
Zero retentionNo training
| Provider | Maximum context | Max output | p50 latency | p50 throughput | 24h uptime | Input / 1M tokens | Output / 1M tokens | Privacy |
|---|---|---|---|---|---|---|---|---|
Bedrock | 131.1K | 131.1K | 156 ms | 143.0 t/s | 100.000% | $0.06 | $0.23 | |
Deepinfra | 131.1K | 131.1K | 262 ms | 96.0 t/s | 100.000% | $0.04 | $0.16 |
What can this model do?
Available modalities and capabilities across inference providers.
TextAdvanced reasoningTool useTools
Technical profile
- Model type
- Language model
- Release date
- Aug 18, 2025
- Knowledge cutoff
- —
- Regions
- —
- API specifications
- V2, V3, V4
- Temperature control
- Supported
Model identifier
nvidia/nemotron-nano-9b-v2Model profile updated: Sep 12, 2026, 1:46 PM
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