GPT-5 nano vs Nemotron Nano 12B VL: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for GPT-5 nano (OpenAI) and Nemotron Nano 12B VL (Nvidia NIM). 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)

OpenAIGPT-5 nanoNvidia NIMNemotron Nano 12B VL

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: GPT-5 nano at $2.50/mo — save 50.0% vs Nemotron Nano 12B VL

							Alert
BestGPT-5 nano	OpenAI	$2.50	$0.000250	$0.50	$2.00	50.0%	Alerts coming soon
Nemotron Nano 12B VL	Nvidia NIM	$5.00	$0.000500	$2.00	$3.00	—	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	GPT-5 nano	Nemotron Nano 12B VL	Cheaper
Input (standard)	$0.05/M	$0.20/M	GPT-5 nano
Output	$0.40/M	$0.60/M	GPT-5 nano
Cached input	$0.01/M	N/A	—

Prices last verified: 2026-03-06 – 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	GPT-5 nanoMonthly	Nemotron Nano 12B VLMonthly	GPT-5 nanoPer request	Nemotron Nano 12B VLPer request
1K requests/mo	$0.25	$0.50	$0.000250	$0.000500
10K requests/mo	$2.50	$5.00	$0.000250	$0.000500
100K requests/mo	$25.00	$50.00	$0.000250	$0.000500
1M requests/mo	$250.00	$500.00	$0.000250	$0.000500

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 GPT-5 nano

by OpenAI

Text classification
Data extraction

Input / 1M tokens

$0.05/M

Output / 1M tokens

$0.40/M

Context window

400,000

Tier

budget

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

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	GPT-5 nano	Nemotron Nano 12B VL
Context window	400,000 tokens	128,000 tokens
Max output tokens	128,000 tokens	8,192 tokens
Performance tier	Budget	Budget
Vision / image input	Yes	Yes
Function calling	Yes	Yes
JSON mode	Yes	Yes
Prompt caching	Yes	No
Batch API (50% discount)	No	No
Extended reasoning	No	No
Fine-tuning	No	No
Rate limit (req/min)	10,000	Not published

GPT-5 nano notes

Cheapest GPT-5 model. 1M context at budget pricing.

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.

Frequently Asked Questions

Is GPT-5 nano cheaper than Nemotron Nano 12B VL?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), GPT-5 nano costs $25.00/month versus $50.00/month for Nemotron Nano 12B VL — a 50% 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, GPT-5 nano or Nemotron Nano 12B VL?

GPT-5 nano has a larger context window at 400,000 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 GPT-5 nano and Nemotron Nano 12B VL support the Batch API?

Neither GPT-5 nano nor Nemotron Nano 12B VL currently supports a batch API with discounted pricing. For batch-eligible alternatives, consider models from OpenAI, Anthropic, or Google that include batch API support.

Which model offers better prompt caching?

GPT-5 nano supports prompt caching at $0.01/M for cached input, while Nemotron Nano 12B VL does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-5 nano's caching capability can substantially reduce effective costs.

What are the best use cases for GPT-5 nano vs Nemotron Nano 12B VL?

Both models are well-suited for Data extraction. GPT-5 nano is particularly strong for Text classification. Nemotron Nano 12B VL is favored for Content Creation, General chatbot. 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 GPT-5 nano vs Nemotron Nano 12B VL?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-5 nano costs $0.000250 per request and Nemotron Nano 12B VL costs $0.000500 per request. At 100,000 requests/month, that translates to $25.00 and $50.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

GPT-5 nano vs Nemotron Nano 12B VL: Summary

When comparing GPT-5 nano and Nemotron Nano 12B VL for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. GPT-5 nano offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $25.00/month, compared to $50.00/month for Nemotron Nano 12B VL.

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-5 nano charges $0.05/M for input tokens and $0.40/M for output tokens. Nemotron Nano 12B VL charges $0.20/M input and $0.60/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 GPT-5 nano 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: GPT-5 nano supports up to 400,000 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 mini vs GPT-5 nano GPT-4o mini vs GPT-5 nano GPT-4.1 mini vs GPT-5 nano GPT-4.1 nano vs GPT-5 nano GPT-5 vs Nemotron Nano 12B VL GPT-5 mini vs Nemotron Nano 12B VL GPT-4o vs Nemotron Nano 12B VL GPT-4o mini vs Nemotron Nano 12B VL

Related Provider Pages

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

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

Relevant Use Cases

See cost recommendations for workloads where GPT-5 nano or Nemotron Nano 12B VL is recommended.

Data Extraction General Chatbot Text Classification