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nvidia/Nemotron-3-Nano-30B-A3B:flex

DeepInfra Inc./πŸ‡ΊπŸ‡Έ US/chat

NVIDIA Nemotron 3 Nano is an open small reasoning model optimized for fast, cost-efficient inference in agentic and production workloads. Built with a hybrid Mixture-of-Experts (MoE) and Mamba-Transformer architecture, it delivers strong multi-step reasoning, high token throughput, stable latency with predictable cost, and efficient deployment for agent-based systems. Designed for real-world AI systems where reasoning can generate significantly more tokens per prompt, Nemotron Nano reduces compuMore

Which id to call

deepinfra/nvidia/Nemotron-3-Nano-30B-A3B:flex

This exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.

Input /1M

$0.04

DeepInfra Inc.

Output /1M

$0.16

4.0x input

Context

262K

tokens

Added

Dec 2025

chat

Capabilities 2/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What nvidia/Nemotron-3-Nano-30B-A3B:flex costs

Provider prices per 1M tokens, updated September 28, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.04

Output /1M

$0.16

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.0056
1M input + 100K output
$0.0560
10M input + 1M output
$0.56

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to deepinfra/nvidia/Nemotron-3-Nano-30B-A3B:flex. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="deepinfra/nvidia/Nemotron-3-Nano-30B-A3B:flex", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window262K tokens
Max output-
API typechat
AddedDec 2025
Model id
Data retentionNone
Used for trainingNo
Served fromπŸ‡ΊπŸ‡Έ US

Public leaderboards

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

No benchmarks are published for this exact variant yet.

Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the DeepInfra Inc. models overview.

Same provider

More from DeepInfra Inc.

Newest first, on the same provider and the same key.

Reference

nvidia/Nemotron-3-Nano-30B-A3B:flex questions

How much does nvidia/Nemotron-3-Nano-30B-A3B:flex cost?

nvidia/Nemotron-3-Nano-30B-A3B:flex is priced at $0.04 per million input tokens and $0.16 per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of nvidia/Nemotron-3-Nano-30B-A3B:flex?

nvidia/Nemotron-3-Nano-30B-A3B:flex has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.

What can nvidia/Nemotron-3-Nano-30B-A3B:flex do?

nvidia/Nemotron-3-Nano-30B-A3B:flex supports tool calling, extended reasoning. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use nvidia/Nemotron-3-Nano-30B-A3B:flex with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/nvidia/Nemotron-3-Nano-30B-A3B:flex". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run nvidia/Nemotron-3-Nano-30B-A3B:flex through Requesty?

Yes. nvidia/Nemotron-3-Nano-30B-A3B:flex runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/nvidia/Nemotron-3-Nano-30B-A3B:flex", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call nvidia/Nemotron-3-Nano-30B-A3B:flex through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.