DeepSeek V3.2 vs Nemotron Super 49B: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for DeepSeek V3.2 (DeepSeek) and Nemotron Super 49B (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
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: Nemotron Super 49B at $3.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestNemotron Super 49B | Nvidia NIM | $3.00 | $0.000300 | $1.00 | $2.00 | 38.8% | Alerts coming soon |
DeepSeek V3.2 | DeepSeek | $4.90 | $0.000490 | $2.80 | $2.10 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | DeepSeek V3.2 | Nemotron Super 49B | Cheaper |
|---|---|---|---|
| Input (standard) | $0.28/M | $0.10/M | Nemotron Super 49B |
| Output | $0.42/M | $0.40/M | Nemotron Super 49B |
| Cached input | $0.03/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 | DeepSeek V3.2Monthly | Nemotron Super 49BMonthly | DeepSeek V3.2Per request | Nemotron Super 49BPer request |
|---|---|---|---|---|
| 1K requests/mo | $0.49 | $0.30 | $0.000490 | $0.000300 |
| 10K requests/mo | $4.90 | $3.00 | $0.000490 | $0.000300 |
| 100K requests/mo | $49.00 | $30.00 | $0.000490 | $0.000300 |
| 1M requests/mo | $490.00 | $300.00 | $0.000490 | $0.000300 |
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 tokensWhen 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 Super 49B
by Nvidia NIM
- General chatbot
- Content Creation
- Summarization
Input / 1M tokens
$0.10/M
Output / 1M tokens
$0.40/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 | DeepSeek V3.2 | Nemotron Super 49B |
|---|---|---|
| Context window | 128,000 tokens | 128,000 tokens |
| Max output tokens | 8,192 tokens | 8,192 tokens |
| Performance tier | Premium | Budget |
| Vision / image input | No | No |
| 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 |
DeepSeek V3.2 notes
V3.2 unified pricing. Off-peak pricing (16:30-00:30 UTC) offers further discounts.
Nemotron Super 49B notes
Nemotron Super 49B on NVIDIA NIM. Budget-tier foundation model with TensorRT-LLM optimization for high-throughput inference on NVIDIA infrastructure.
Frequently Asked Questions
Is DeepSeek V3.2 cheaper than Nemotron Super 49B?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Nemotron Super 49B costs $30.00/month versus $49.00/month for DeepSeek V3.2 — a 39% 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 Super 49B?
Both DeepSeek V3.2 and Nemotron Super 49B have the same context window: 128,000 tokens.
Do DeepSeek V3.2 and Nemotron Super 49B support the Batch API?
Neither DeepSeek V3.2 nor Nemotron Super 49B 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 Super 49B 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 Super 49B?
Both models are well-suited for General chatbot. DeepSeek V3.2 is particularly strong for Code generation, Content & copywriting. Nemotron Super 49B is favored for Content Creation, Summarization. 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 Super 49B?
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 Super 49B costs $0.000300 per request. At 100,000 requests/month, that translates to $49.00 and $30.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
DeepSeek V3.2 vs Nemotron Super 49B: Summary
When comparing DeepSeek V3.2 and Nemotron Super 49B for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Nemotron Super 49B offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $30.00/month, compared to $49.00/month for DeepSeek V3.2.
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 Super 49B charges $0.10/M input and $0.40/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 DeepSeek V3.2 but not Nemotron Super 49B. 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.
Related Comparisons
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 Super 49B is recommended.