NVIDIA-Nemotron-Nano-9B-v2
deepinfra · chat model
NVIDIA-Nemotron-Nano-9B-v2 is listed here as a chat model from deepinfra. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Input
$0.0400 / 1M tokens
Output
$0.1600 / 1M tokens
Cached input
N/A
Context
131.1K
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.0400 / 1M tokens |
| Output | $0.1600 / 1M tokens |
| Embedding | $0.0400 / 1M tokens |
Token limits
Context window
131.1K
Max input tokens
131.1K
Max output tokens
131.1K
Max tokens
131.1K
Capabilities
| Capability | Supported |
|---|---|
| Vision | — |
| Function calling | ✅ |
| Parallel function calling | — |
| Tool choice | ✅ |
| Prompt caching | — |
| Reasoning | — |
| Response schema | — |
| System messages | — |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| MT-Bench | 8.22 | total | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| IFEval | 79.9 | Prompt-Strict Acc | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| IFEval | 86.1 | Instruction-Strict Acc | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| MMLU | 78.7 | 0-shot | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| GSM8K | 92.3 | 0-shot | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| HumanEval | 73.2 | 0-shot | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| MBPP | 75.4 | 0-shot | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| Arena Hard | 54.2 | Arena Hard | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| AlpacaEval 2.0 LC | 41.5 | Length Controlled | Base model: Nemotron (Nemotron-4-340B-Instruct) | 2026-05-31 | Link |
| AIME 2025 | 76.25% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| MATH-500 | 97.75% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| GPQA | 64.48% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| LCB | 70.79% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| BFCL | 66.98% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| IFEval Prompt | 84.70% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
| IFEval Instruction | 89.81% | Reasoning On | Base model: Nemotron (NVIDIA-Nemotron-Nano-12B-v2) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Docs
| Official docs |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| NVIDIA-Nemotron-Nano-9B-v2 deepinfra | In $0.0400 / 1M tokens Out $0.1600 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| gpt-oss-20b deepinfra | In $0.0400 / 1M tokens Out $0.1500 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 99% |
| gpt-oss-120b deepinfra | In $0.0500 / 1M tokens Out $0.4500 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 91% |
| Meta-Llama-3.1-8B-Instruct deepinfra | In $0.0300 / 1M tokens Out $0.0500 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 90% |
| Meta-Llama-3.1-70B-Instruct-Turbo deepinfra | In $0.1000 / 1M tokens Out $0.2800 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 90% |
| Llama-3.3-Nemotron-Super-49B-v1.5 deepinfra | In $0.1000 / 1M tokens Out $0.4000 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 88% |
| DeepSeek-R1-Distill-Qwen-32B deepinfra | In $0.2700 / 1M tokens Out $0.2700 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 88% |
| gemma-3-27b-it deepinfra | In $0.0900 / 1M tokens Out $0.1600 / 1M tokens | text image
Output: text | Function callingTool choice | 131.1K | Same provider Overall 83% |
| gemma-3-4b-it deepinfra | In $0.0400 / 1M tokens Out $0.0800 / 1M tokens | text image
Output: text | Function callingTool choice | 131.1K | Same provider Overall 83% |
| gemma-3-12b-it deepinfra | In $0.0500 / 1M tokens Out $0.1000 / 1M tokens | text image
Output: text | Function callingTool choice | 131.1K | Same provider Overall 82% |
| phi-4 deepinfra | In $0.0700 / 1M tokens Out $0.1400 / 1M tokens | text
Output: text | Function callingTool choice | 16.4K | Same provider Overall 82% |
| Mistral-Small-3.2-24B-Instruct-2506 deepinfra | In $0.0750 / 1M tokens Out $0.2000 / 1M tokens | text image
Output: text | Function callingTool choice | 128.0K | Same provider Overall 81% |
| Phi-4 azure_ai | In $0.1250 / 1M tokens Out $0.5000 / 1M tokens | text
Output: text | Function callingTool choice | 16.4K | Text covered Overall 73% |
| Llama-3.3-70B-Instruct azure_ai | In $0.7100 / 1M tokens Out $0.7100 / 1M tokens | text
Output: text | Function callingTool choice | 2.0K | Text covered Overall 68% |
| mistral-nemo novita | In $0.0400 / 1M tokens Out $0.1700 / 1M tokens | text
Output: text | Tool choice | 16.0K | Text covered Overall 67% |
| gpt-3.5-turbo Azure | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 67% |
| gpt-35-turbo Azure | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 67% |
| gpt-35-turbo-16k-0613 Azure | In $3.0000 / 1M tokens Out $4.0000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 66% |
| apac.amazon.nova-micro-v1:0 bedrock_converse | In $0.0370 / 1M tokens Out $0.1480 / 1M tokens | text
Output: text | Function calling | 10.0K | Text covered Overall 66% |
| gpt-4-0613 Azure | In $30.0000 / 1M tokens Out $60.0000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 66% |
| gpt-oss-20b novita | In $0.0400 / 1M tokens Out $0.1500 / 1M tokens | text image
Output: text | Tool choice | 32.8K | Text covered Overall 55% |
| gpt-oss-20b ovhcloud | In $0.0400 / 1M tokens Out $0.1500 / 1M tokens | text
Output: unknown | Low overlap | 131.0K | Partial I/O overlap Overall 34% Missing text |
| qwen3-8b llamagate | In $0.0400 / 1M tokens Out $0.1400 / 1M tokens | text
Output: unknown | Function calling | 8.2K | Partial I/O overlap Overall 28% Missing text |
No models match this filter.