Nemotron Nano 12B VL vs o4-mini: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Nemotron Nano 12B VL (Nvidia NIM) and o4-mini (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Mar 11, 2026

Interactive Cost Calculator

Select Models (2/10)

Nvidia NIMNemotron Nano 12B VLOpenAIo4-mini

Use Case Preset

Fills in typical token counts for a workload type

Avg Input Tokens / Request

Tokens in each prompt sent to the model

Avg Output Tokens / Request

Tokens generated in each response

Monthly Requests

Total API calls per month

Cheapest: Nemotron Nano 12B VL at $5.00/mo — save 84.8% vs o4-mini

							Alert
BestNemotron Nano 12B VL	Nvidia NIM	$5.00	$0.000500	$2.00	$3.00	84.8%	Alerts coming soon
o4-mini	OpenAI	$33.00	$0.003300	$11.00	$22.00	—	Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing Type	Nemotron Nano 12B VL	o4-mini	Cheaper
Input (standard)	$0.20/M	$1.10/M	Nemotron Nano 12B VL
Output	$0.60/M	$4.40/M	Nemotron Nano 12B VL
Cached input	N/A	$0.28/M	—
Batch input	N/A	$0.55/M	—
Batch output	N/A	$2.20/M	—

Prices last verified: 2026-03-08 – 2026-03-11

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

Volume	Nemotron Nano 12B VLMonthly	o4-miniMonthly	Nemotron Nano 12B VLPer request	o4-miniPer request
1K requests/mo	$0.50	$3.30	$0.000500	$0.003300
10K requests/mo	$5.00	$33.00	$0.000500	$0.003300
100K requests/mo	$50.00	$330.00	$0.000500	$0.003300
1M requests/mo	$500.00	$3,300.00	$0.000500	$0.003300

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose Nemotron Nano 12B VL

by Nvidia NIM

Content Creation
Data extraction
General chatbot

Input / 1M tokens

$0.20/M

Output / 1M tokens

$0.60/M

Context window

128,000

Tier

budget

When to Choose o4-mini

by OpenAI

Code generation
Data extraction

Input / 1M tokens

$1.10/M

Output / 1M tokens

$4.40/M

Context window

200,000

Tier

reasoning

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

Capability	Nemotron Nano 12B VL	o4-mini
Context window	128,000 tokens	200,000 tokens
Max output tokens	8,192 tokens	100,000 tokens
Performance tier	Budget	Reasoning
Vision / image input	Yes	Yes
Function calling	Yes	Yes
JSON mode	Yes	Yes
Prompt caching	No	Yes
Batch API (50% discount)	No	Yes
Extended reasoning	No	Yes
Fine-tuning	No	No
Rate limit (req/min)	Not published	1,000

Nemotron Nano 12B VL notes

Nemotron Nano 12B VL on NVIDIA NIM. Budget-tier multimodal model supporting vision inputs, optimized for efficient image-and-text inference on NVIDIA hardware.

o4-mini notes

Configurable reasoning effort. Best budget reasoning model from OpenAI.

Frequently Asked Questions

Is Nemotron Nano 12B VL cheaper than o4-mini?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Nemotron Nano 12B VL costs $50.00/month versus $330.00/month for o4-mini — a 85% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, Nemotron Nano 12B VL or o4-mini?

o4-mini has a larger context window at 200,000 tokens, compared to 128,000 tokens for Nemotron Nano 12B VL. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do Nemotron Nano 12B VL and o4-mini support the Batch API?

o4-mini supports the Batch API (50% discount for async processing), while Nemotron Nano 12B VL does not. If your workload tolerates up to 24-hour latency, routing to o4-mini with batch pricing could significantly cut costs versus Nemotron Nano 12B VL's standard rate.

Which model offers better prompt caching?

o4-mini supports prompt caching at $0.28/M for cached input, while Nemotron Nano 12B VL does not offer prompt caching. For RAG applications or chatbots with large, repeated context, o4-mini's caching capability can substantially reduce effective costs.

What are the best use cases for Nemotron Nano 12B VL vs o4-mini?

Both models are well-suited for Data extraction. Nemotron Nano 12B VL is particularly strong for Content Creation, General chatbot. o4-mini is favored for Code generation. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.

What is the cost per request for Nemotron Nano 12B VL vs o4-mini?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Nemotron Nano 12B VL costs $0.000500 per request and o4-mini costs $0.003300 per request. At 100,000 requests/month, that translates to $50.00 and $330.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Nemotron Nano 12B VL vs o4-mini: Summary

When comparing Nemotron Nano 12B VL and o4-mini for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Nemotron Nano 12B VL offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $50.00/month, compared to $330.00/month for o4-mini.

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Nemotron Nano 12B VL charges $0.20/M for input tokens and $0.60/M for output tokens. o4-mini charges $1.10/M input and $4.40/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Prompt caching is supported by o4-mini but not Nemotron Nano 12B VL. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: o4-mini supports up to 200,000 tokens in a single request, versus 128,000 tokens for Nemotron Nano 12B VL. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

GPT-5 vs Nemotron Nano 12B VL GPT-5 mini vs Nemotron Nano 12B VL GPT-5 nano vs Nemotron Nano 12B VL GPT-4o vs Nemotron Nano 12B VL GPT-5.4 vs o4-mini GPT-5.4 Pro vs o4-mini GPT-5.3 vs o4-mini GPT-5.2 vs o4-mini

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Nvidia NIM API Pricing — All Models OpenAI API Pricing — All Models

Relevant Use Cases

See cost recommendations for workloads where Nemotron Nano 12B VL or o4-mini is recommended.

Code Generation Data Extraction General Chatbot