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DeepSeek V3.2 vs Nemotron Nano 12B VL: API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for DeepSeek V3.2 (DeepSeek) 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

DeepSeekDeepSeek V3.2Nvidia NIMNemotron Nano 12B VL

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: DeepSeek V3.2 at $4.90/month.

Cheapest: DeepSeek V3.2 at $4.90/mo — save 2.0% vs Nemotron Nano 12B VL
Alert
BestDeepSeek V3.2
DeepSeek$4.90$0.000490$2.80$2.102.0%Alerts coming soon
Nemotron Nano 12B VL
Nvidia NIM$5.00$0.000500$2.00$3.00Alerts 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 TypeDeepSeek V3.2Nemotron Nano 12B VLCheaper
Input (standard)$0.28/M$0.20/MNemotron Nano 12B VL
Output$0.42/M$0.60/MDeepSeek V3.2
Cached input$0.03/MN/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.

VolumeDeepSeek V3.2MonthlyNemotron Nano 12B VLMonthlyDeepSeek V3.2Per requestNemotron Nano 12B VLPer request
1K requests/mo$0.49$0.50$0.000490$0.000500
10K requests/mo$4.90$5.00$0.000490$0.000500
100K requests/mo$49.00$50.00$0.000490$0.000500
1M requests/mo$490.00$500.00$0.000490$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 DeepSeek V3.2

by DeepSeek

  • Code generation
  • Content & copywriting
  • General chatbot

Input / 1M tokens

$0.28/M

Output / 1M tokens

$0.42/M

Context window

128,000

Tier

premium

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.

CapabilityDeepSeek V3.2Nemotron Nano 12B VL
Context window128,000 tokens128,000 tokens
Max output tokens8,192 tokens8,192 tokens
Performance tierPremiumBudget
Vision / image inputNoYes
Function callingYesYes
JSON modeYesYes
Prompt cachingYesNo
Batch API (50% discount)NoNo
Extended reasoningNoNo
Fine-tuningNoNo

DeepSeek V3.2 notes

V3.2 unified pricing. Off-peak pricing (16:30-00:30 UTC) offers further discounts.

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 DeepSeek V3.2 cheaper than Nemotron Nano 12B VL?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), DeepSeek V3.2 costs $49.00/month versus $50.00/month for Nemotron Nano 12B VL — a 2% 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, DeepSeek V3.2 or Nemotron Nano 12B VL?

Both DeepSeek V3.2 and Nemotron Nano 12B VL have the same context window: 128,000 tokens.

Do DeepSeek V3.2 and Nemotron Nano 12B VL support the Batch API?

Neither DeepSeek V3.2 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?

DeepSeek V3.2 supports prompt caching at $0.03/M for cached input, while Nemotron Nano 12B VL does not offer prompt caching. For RAG applications or chatbots with large, repeated context, DeepSeek V3.2's caching capability can substantially reduce effective costs.

What are the best use cases for DeepSeek V3.2 vs Nemotron Nano 12B VL?

Both models are well-suited for General chatbot. DeepSeek V3.2 is particularly strong for Code generation, Content & copywriting. Nemotron Nano 12B VL is favored for Content Creation, Data extraction. 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 DeepSeek V3.2 vs Nemotron Nano 12B VL?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — DeepSeek V3.2 costs $0.000490 per request and Nemotron Nano 12B VL costs $0.000500 per request. At 100,000 requests/month, that translates to $49.00 and $50.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

DeepSeek V3.2 vs Nemotron Nano 12B VL: Summary

When comparing DeepSeek V3.2 and Nemotron Nano 12B VL for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. DeepSeek V3.2 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $49.00/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. DeepSeek V3.2 charges $0.28/M for input tokens and $0.42/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 DeepSeek V3.2 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: Both models support 128,000 tokens per request. 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.

Related Provider Pages

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

Relevant Use Cases

See cost recommendations for workloads where DeepSeek V3.2 or Nemotron Nano 12B VL is recommended.